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Utilizing networks and digital distribution strategies to create spreadable video content for change

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Utilizing networks and digital distribution strategies to create spreadable video content for change

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UTILIZING NETWORKS AND DIGITAL DISTRIBUTION STRATEGIES TO
CREATE SPREADABLE VIDEO CONTENT FOR CHANGE

By

Emily Gee

A Thesis Presented To The
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements of the Degree of
MASTERS OF ARTS
(STRATEGIC PUBLIC RELATIONS)

December 2014

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ACKNOWLEDGEMENTS
Thank you to all who helped gather the materials and knowledge necessary to build an
effort that will help non-profit organizations engage and expand networks. I feel there is an
immense and influential role digital media, specifically videos, can play in creating an
emotional connection with supporters and donors. This thesis is an effort to help understand
how organizations can capitalize on the expanding idea of spreadability and virality online.
I truly appreciate the time interviewees, case study participants and professors spent to
make this thesis usable and functional research. A big thank you to the thousands of social
good activists that work hard to promote causes they believe in. While this is by no means an
exhaustive list of case studies and findings, I hope the research helps spark excitement and
creativity in the possibilities of spreading social good content online.

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TABLE OF CONTENTS
Executive Summary ........................................................................................................................ 4
Chapter 1: Introduction ................................................................................................................. 6
The Dilemma ................................................................................................................................ 6
The Want To Do Good ................................................................................................................. 9
Are Videos Really That Important? ............................................................................................ 10
Chapter 2: The Factors ................................................................................................................. 12
Factor One: Content .................................................................................................................... 12
Factor Two: Networks ................................................................................................................ 14
Factor Three: Distribution .......................................................................................................... 20
Videos Have The Ability To Create Change .............................................................................. 23
YouTube As A Platform For Social Change: KONY 2012 ........................................................ 24
Chapter 3: Methods ...................................................................................................................... 28
Understanding Factor One: Content ........................................................................................... 29
Understanding Factor Two: Networks ........................................................................................ 30
Understanding Factor Three: Distribution .................................................................................. 30
Chapter 4: Case Studies ............................................................................................................... 32
Case Study 1: Children’s Hospital Los Angeles ......................................................................... 32
Factor One: Content ........................................................................................................... 32
Factor Two: Networks ........................................................................................................ 34
Factor Three: Distribution .................................................................................................. 36
Recommendations .............................................................................................................. 39
Case Study 2: Make-A-Wish ...................................................................................................... 41
Factor One: Content ........................................................................................................... 41
Factor Two: Networks ........................................................................................................ 43
Factor Three: Distribution .................................................................................................. 45
Recommendations .............................................................................................................. 48
Case Study 3: People For The Ethical Treatment of Animals (PETA) ...................................... 50
Factor One: Content ........................................................................................................... 50
Factor Two: Networks ........................................................................................................ 52
Factor Three: Distribution .................................................................................................. 54
Recommendations .............................................................................................................. 56
Case Study 4: Grades of Green ................................................................................................... 58
Factor One: Content ........................................................................................................... 58
Factor Two: Networks ........................................................................................................ 59
Factor Three: Distribution .................................................................................................. 60
Recommendations .............................................................................................................. 61
Chapter 5: Conclusion .................................................................................................................. 63
Citations ......................................................................................................................................... 66
Appendix ........................................................................................................................................ 69
Appendix 1: Top 10 Tips to Spread Media ................................................................................. 69
Appendix 2: Interview Questionairre and Notes ........................................................................ 71
Appendix 3: Content Analysis .................................................................................................... 76
Appendix 4: Buzzwords Defined ................................................................................................ 77
Appendix 5: Beyond The Hypothetical ...................................................................................... 78

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EXECUTIVE SUMMARY
Not all recommendations are created equal. A close friend or family member’s
recommendations come with a seal of approval, an extra emphasis that makes us more likely
to trust or try what they recommend. This idea holds true in everyday life and
recommendations via social media. People value what peers recommend, and when we share
a video or retweet a link we are, in fact, spreading content to our online friends, or our
network. The acts of sharing, retweeting, and “liking” speak directly to our ability to
recommend and spread content. Consumers have become powerful brand advocates because
they, in part, control the “spreadability” of online content. This thesis explores how
spreadability occurs with causes and non-profit videos on YouTube.
Video content creation is the most-used media technique for non-profit organizations
(GAP VIII). The desire to create highly impactful and engaging cause videos is a recent trend
that is making the “Social Good Videos” category the fastest growing section on YouTube.
However, how do we know when a video has succeeded? Is it by the number of people who
view a cause video? Is it the number of comments it receives? Maybe how many times it is
recommended to friends? True engagement with video content may be more difficult to
achieve than metrics alone. And, it requires a coordinated strategy from the beginning of idea
creation to video editing to distribution.
This thesis uses network theory to examine how non-profit organizations and causes
can use social networks, in particular YouTube, to achieve spreadability for their content.
While buzzwords like “going viral” have become an objective for public relations
practitioners, the author argues that true spreadable media becomes successful when great
content meets a compatible and connected network through a coordinated and

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interdepartmental effort. Further, the thesis outlines the importance of three factors (factor
one: video content, factor two: social networks, factor three: video distribution) in the
research and case studies below.
Of course, the equation of great video content + compatible network type +
coordinated distribution strategy is easier said than done. To help visualize how this happens
the author first investigates prior research in video creation and analyzes KONY 2012, a video
that is the epitome of what many causes strive to achieve: great visuals, millions of views and
Internet virality. While the video’s content ultimately became controversial in the world of
cause advocacy, its ability to generate viewership is unparalleled in cause marketing.
After unpacking the KONY 2012 example, the author will discuss four key case
studies from non-profits at different developmental stages. Understanding each non-profit’s
social network and YouTube channel will show how their networks utilize video content to
maximize exposure. Analyzing the intricacies of networks and video characteristics like video
quality and emotional appeals will help show how videos spread across the Internet. After
comparing the case studies and interviews with experts in the digital strategy and video
content fields, the author will examine the overall takeaways and characteristics that create
the most spreadable, viral content possible.
This thesis is written to help non-profit and cause-related organizations achieve
success in digital marketing and, specifically, video content creation. By examining the case
studies and key takeaways, the author hopes to present an informative, but by no means
exhaustive, way to capitalize on spreadability of video content for non-profit and cause
related organizations.

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CHAPTER 1: INTRODUCTION
The Dilemma
Why do certain cause-related videos spread like wildfire through social network
channels and others remain merely stagnate, or worse, enter into the abyss of YouTube? We
have all seen the videos that are recommended by one friend, and then a few hours later, 10
more friends have recommended it. How does this happen to social good videos, and what
separates the good, the bad and the videos that are just plain unseen. The goal of this thesis is
to analyze the nuanced differences that make some social good videos succeed while others
do not.
While it would be ideal to provide non-profit organizations with an equation to
achieve viral video success, an exact equation may be hard to pinpoint. Mix two parts positive
emotion with one part attention grabbing calls to action and add a hint of immediacy to
increase video engagement by 300%. While no exact equation exists, what we can do is
analyze case studies and past examples to understand what characteristics are likely to help
create success. Viral video success stems from dozens of factors, some of which are within
our control. We can control the emotions, the length of the video, the key words and tags, and
many other valuable pieces of the virality puzzle to help steer a video in the direction of
spreadability.
This key combination of video content (factor one), network coordination (factor two)
and strategized distribution (factor three) can be defined and created in many ways. While we
have tendencies to measure online video success in terms of the number of views, true
engagement goes much deeper. How long did the user watch the video? Did he or she click on
the organization’s website after watching? Did the viewer “like” the video or, better yet, share

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it with friends? Did viewers donate or did they simply watch five seconds of the video and
log-off? These questions help determine the true user engagement, but usually remain
unanswered in the non-profit world.
The recent shift to video content creation stems from a broader trend that visual,
dynamic content is more impactful than solely text-based posts. GAP VIII, a recent survey of
top PR practitioners, suggests that video content creation is the most used media tactic in
public relations (GAP VIII). Platforms like Instagram, with its ability to create video content
and Vine, with its focus on video sharing, have made it easier than ever to produce video
content. More specifically, social good videos are also on the rise. The success of cause-
related video sites like Upworthy and GOOD suggest that videos play an increasingly key role
in promoting causes. Couple these trends with our want for immediate information and
simplicity, and there is additional pressure to make quick, impactful videos -- and do it well --
and do it big.
Often, having content that is featured on sites like Upworthy or GOOD can be the
“breakthrough” causes need to spread their content to the masses. However, it is difficult to
rely on the mere chance that these sites will post and spread content, as there are so many
great causes to choose to promote. It is much more likely that non-profit organizations can
create videos with the purpose of spreading the content through their own network. Networks,
or the group of followers who interact with the content, hold the power to help content spread.
As the content creators and strategists, public relations practitioners also have the ability to
make content compelling, easy to share and ripe for spreading through our social networks.
This is exemplified by the analogy of how a secret might spread in a group of friends
(a tight network of friends) versus how a secret might spread through randomly chosen people

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(a loose group of collected people). If we told the secret to a stranger in the loose network,
there is little likelihood that he or she would care at all about the secret, let alone care enough
to tell another person. Even if another person was told, it is likely the secret would end.
However, if the same secret was told to a close friend, it is more likely the friend would care,
and more likely that he or she had mutual friends who would also be interested. By the end of
the week there could be a dozen people within your network who have heard the secret. Now,
we couple telling that friend a secret with a bit of strategy. Instead of telling one random
friend, what if we told the friend who has the most friends and influence, or the biggest
network. Choosing the right friend, a “node” in networking terms, is a crucial part of
spreadability in a network. Just as we can prime a secret to spread in a group of friends, we
can prime a video to spread through a network of advocates. However, in order to spread
content through a network, the first step is to understand the relationships and opinion leaders
within that network.
We can often predict the success of a video based on our network base, and
engagement and networking type, just as we can predict if a secret will spread through a
group of friends. This thesis will specifically analyze how a non-profit’s network and video
content creation interacts to achieve spreadable media. The following primary and secondary
research and original case studies help us concentrate on the three factors (content creation,
networks and distribution) that lead to how video content flows through networks, and how
we can improve spreadability.

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The Want To Do Good
Before we can begin to understand non-profit networks, we must first understand the
nature of non-profits and cause groups. People who run non-profit organizations have an
inherent “want” for their causes to be heard and to make a difference. However, with almost
1.5 million registered 501C3 organizations in the United States, people are constantly
bombarded with messages from do-good organizations (Foundation Center, 2013). While we
may like to think doing good -- or great -- work is enough to create something that spreads
through the Internet, the truth is that the goal of spreadability can be much more difficult to
achieve. Contributing to a great cause is not enough to create spreadable media on the
Internet.
Instead, there is a combination of factors that affect how likely a video is to spread on
the Internet. The first factor is the content of the video. The quality of the video, the emotional
appeal and the length of the video, among other characteristics, affect how well it is received
and how likely it is to spread. The second factor is the network in which the video is exposed.
The amount of friends, followers, and advocates who view the video is partially based on the
awareness and engagement of the audience. The third factor in the spreadability of online
video content is how the video is distributed. There are two types of distribution directions:
push or pull distribution. Pull distribution relies on keywords and tagging for how to best
bring content to the audience. For example, search engines like Google and Bing are ways
audience members find content themselves. Push distribution relies on social and traditional
media to push out content, brining content directly to audience members. All three of these
factors, video content, network and video distribution, describe the basis of how to create
spreadable media.

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Are Videos Really That Important?
Before understanding the factors involved in creating spreadable video content, one
may be thinking: why are videos so important? Why not study the spreadability of social good
news stories or pictures on Facebook? The answer is that videos seem to be more than just the
latest trend in the non-profit sphere; video content is set to be the next wave in the future of
digital media.
“Nonprofits and Activism” and “Education” are the two fastest-growing categories on
YouTube (Rhamin, 2012). Over one trillion YouTube videos were viewed in 2011, and an
average of 140 YouTube videos are viewed annually per person worldwide. Before YouTube
became popular, causes and advocacy groups turned to public service announcements (PSAs)
to share their stories via video technology. While the effectiveness of PSAs has been debated
for years (Dillard, 2000 and Fishbein and Martin et al, 2002), there is strong agreement
among campaign designers that the visual elements of PSAs have the ability to trigger intense
emotional and cognitive responses (Bator and Cialdini, 2000). The YouTube platform
combines the visual elements that make PSAs highly desirable with relatively low costs,
thereby promising the possibility of reaching more audience members on a smaller budget.
While YouTube itself is a public platform, not all YouTube videos are created equal
(Cheng, 2008). Sandoval-Alamanzan and Rodrigo highlight a circular effect that can occur on
YouTube via cyberactivism. They suggest that the platform is circular in nature because
similar content is suggested to viewers, making it inherently biased when viewers are only
shown like-minded content. YouTube viewers see “suggested content” that is generated
through a combination of tagged videos and boosted and past-viewed content (Burgess,
2009). This suggests that if people do not search directly for a cause-related video, it will

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most likely not be recommended to them. Therefore, while YouTube as a platform provides
opportunities for publishing videos in an inexpensive way, publishing a video does not
inherently mean that it will be viewed. In fact, it means that, while creating video content may
be the most common media technique in public relations, strategizing content distribution is
where spreadable media becomes exponentially more important.
In addition to creating biased content viewing, YouTube itself is a crowded space that
features an abundance of video content types. YouTube content ranges from videos of babies
and kittens to promotional materials and illegally streaming videos, and, because of this,
viewers have increasingly more ways to spend their time on the site (Lange, 2013; Puck,
2013). The rise in the amount of available video content has created extreme competition for
viewers’ time. No longer does the competition for cause-related videos come solely from
other cause-related videos. They now compete for time against other YouTube videos, other
video sharing sites and the Internet in general. With this influx of direct and indirect
competitors, the pressure to create great videos is increasing. While video bias and extreme
competition does exist within it, the platform is still ripe for creating and spreading social
good content. While there seems to be great potential for spreading cause media on YouTube,
the question remains: how does the video content flow through networks? To better
understand this, the author will break down spreadable online videos into their three factors:
the videos’ content, network and distribution.

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CHAPTER 2: THE FACTORS
Factor One: Content
The first factor that shapes the spreadability of a video is the content itself. There are
many content-related factors that affect how likely a video is to travel through Facebook
pages, into email boxes and via Twitter. One of the main measurements of video content is
how much a video appeals to its target audience. The amount of emotional connection they
feel with the content dramatically alters how likely audience members are to share, or spread,
that content. Before even creating a video, unpacking the power of emotional appeal will help
PR professionals prepare great content that is tailored for spreadability.
Emotional Appeal
Emotional appeal is the reaction that tugs at one’s heart from inside a screen, the
immediate desire to share, the gut feeling that one has seen something truly impactful. The
emotional appeal—the emotions that connect with the target audience—is critically important
in cause-related videos. Without emotional appeal, efforts to create a call to action or generate
support for a cause are likely lost. The American Society for the Prevention of Cruelty of
Animals (ASPCA) has built a following by using the organization’s signature video, which
features dogs locked in shelters and music by Sarah McLachlan. Similarly, Feed The Children
is known for its strong emotional appeals linking to spotlighted stories about children in need.
Both of these causes utilize strong emotional appeals via video to trigger calls to action for
donations and volunteering efforts. The ASPCA was almost able to double its annual budget
in 2008 because of the success of the Sarah McLachlan video, which raised around $20
million dollars (Strom, 2008).

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Much rests on a video’s emotional appeal and its ability to connect with an audience.
Berger and Milkman researched how emotional appeals affect the spreadability of news
articles in the online edition of The New York Times. Interestingly, they found that warm-
hearted, positive news stories are the most likely to spread. However, when stories also
produce a sense of urgency or a direct appeal to the audience, that content is viewed even
more frequently. Like with most aspects of spreadable content research, it seems there is no
exact equation for discovering which emotional content creates the most impact. However,
what is supported is the notion that content filled with joy, urgency or personal appeal is read
the most frequency. Therefore, it is clear that, in order for people to share content, the content
must be compelling enough to create a strong emotional attachment between the viewer and
the video itself.
While Berger and Milkman specifically investigated the role of emotional appeal in
news stories, others have concentrated on studying which video characteristics elicit the
strongest emotional connections. Researchers agree that a combination of visual elements and
verbiage help tell impactful and emotional stories that resonate via online videos. While some
scholars like Brader believe that negative emotions persuade people and motivate them to
action, others do not. For instance, Yoo and MacInnis believe that positive emotions are also
likely to motivate people to participate in a call to action. While emotion and marketing
researchers seem to defend the effects of both positive and negative emotions in emotional
appeal videos, what has been proven is that the use of strong, compelling emotional appeals
creates sustained connections to brands or organizations. Therefore, whether the emotion
expressed is positive or negative, expressing something boldly is much more likely to lead to
long-lasting relationships. Whether by persuading supporters to laugh, tugging at their

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heartstrings or sparking a sense of urgency, creating a compelling story starts with bold
emotional appeals.
Video length is a factor that is growing increasingly more important as people feel a
need for more immediate and faster access to information. While research has shown that
shorter videos tend to spread more rapidly throughout the Internet, standard PSAs fluctuate in
their lengths of time (Xu et al, 2010). PSAs are usually less than one and a half minutes long,
and some can be as short as fifteen seconds. The video length requirements that were
originally developed for televised PSAs no longer apply to online social-cause videos. This
freedom has lead to a variety of video lengths in the field of cause-related content. For
example, on the one hand, the KONY 2012 video is almost thirty minutes long, with millions
of people having watched the thirty-minute video through completion. On the other hand,
sites like Vine encourage content that is less than seven seconds in length. Therefore, while
there is a push to create shorter and shorter content with more impactful and immediate
messaging, YouTube gives people the freedom to create videos like never before. While
shorter video length has become a common “best practice” factor of success, it is possible to
create lengthy content that has the power to spread—and to spread quickly.

Factor Two: Networks
Once the video content characteristics (factor one) have been created, the next factor
to understand is how the video will travel or spread through the Internet. To help demonstrate
why networks are so important, the author will use social network analysis (SNA) to explain
how a network has the ability to spread content.

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Social networks’ shapes and sizes affect the way organizations strategize content. The
stronger an organization’s network is, the more opportunities its content has to spread. What
one would imagine happening in the analogy of telling a friend a secret happens in terms of
sharing video content across networks. If a YouTube video is placed on the Internet without
any connection to other social media, it relies solely on people who may stumble across it to
garner traction. This is very unlikely to happen. Instead, sharing the video with already-
established audience members creates a group of immediate advocates who have a vested
interest in continuing to share the content. Understanding and tapping into established
networks creates a higher likelihood of spreading content, just as sharing a secret with close
friends makes it more likely to travel quickly.
Recent studies have proven that it is possible to create and utilize tight social media
networks for the greater good. The American Heart Association found that patients who
participated in an online social community or social network had a higher rate of commitment
to losing weight (Li et al, 2013). Members of the tight network were able to establish
emotional attachments to each other because they had an innate connection around wanting to
lose weight. This is an example of a tight, interlocked network of advocates. A study by
Bastiampilla found that depression is almost “contagious” in social networks. The more
network relationships that are depressed, the more likely the surrounding nodes are to also
become depressed (Bastiampilla et al, 2012). The same idea works with the spreading of
social good content. The more people there are within networks who have a vested interest in
a cause, the more likely others within that network are to value it. Therefore, social networks
have the ability to form tight units and bonds and to activate these connections to spread
content.

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While social network analysis (SNA) is not traditionally used in non-profit marketing
and communications, the idea of combining SNA technology with communications in the
non-profit realm is on the brink of becoming popular. Beth Kanter discusses the benefits of
network analysis throughout her blog and recent book (Kanter & Paine, 2012). Together,
Kanter and Paine discuss the importance of measurement and SNA in making sure key
messages are being properly targeted. Much like the author of this thesis, Kanter believes that
social network modeling can lead to better understanding of and connection with supporters
and influencers.
In our analogy about a group of friends spreading a secret, the group would be the
network and each individual friend would be what is referred to as a node. The means by
which two of the friends, or nodes, are connected would in turn be called a pathway.
Pathways are very important to spreadable media, and one of the goals of SNA is to track
which pathways have the most influence or spreadability. For example, the opinion leader in
the group of friends has the ability to spread a message to many different people, but knowing
the pathway or direct connection to the influential friend is just as important as telling many
people. When pathways are mapped, clusters then become evident. Clusters form when
groups of people share a similar connection. For example, one could map a group of friends
based on how its members met. Friends might then become clusters based on whether they
met in high school, college or a job. The ways the clusters intertwine become the links
between them. These links are extremely important because they help spread content between
clusters. The more links there are between clusters, the greater ability the content has to
spread outside of its original audience. The MentionMapp data will help demonstrate which
connections have the most links and therefore the most ability to help spread content to new

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network clusters. It is, in fact, these links that hold the power to create content that spreads to
new groups of friends or social networks (John, Carrington, et al; 2011).
Social network analysis can help map a social network by using data to match each
person’s connections to others in one area. The overlapping networks then show which
followers or supporters have the most ties, or connections, to the rest of the network. While
the idea of SNA has been part of the communications dialogue since the 1970s, today’s
technological advancements have made it possible to map networks on a more precise and
detailed basis than ever before (Prell, 2011; Wasserman & Fauster, 1994; Berkowitz, 1988).
SNA mapping technology plots people’s connections with one another and helps show how
information is spread through acquaintances, friends and, therefore, networks. SNA mapping
technology has been used to explain communications phenomena for decades, but it has only
recently been used by non-profits and cause organizations at large.
In 2010, Johnson and Honnold conducted a study of 52 non-profit organizations and
their use of data and network theory. They discovered that, while network theory is not being
used by non-profits as a whole, there are multiple outcomes that make network analysis
helpful to non-profits. Metrics help non-profits raise money, fundraise and meet their mission
goals and objectives. Therefore, while SNA may traditionally be a research component left to
large companies, there are more and more voices arguing for SNA use in the non-profit arena.
While SNA technology may require a bit more knowledge on the front end than
traditional tools, it can guide strategy in a more metrics-based approach. While most people
may not think about networks throughout their daily lives, everyone has a very unique
network of connections depending on their age, geography, education and countless other
measurements. Our networks change over time and have the ability to grow close-knit or

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loose. They become intertwined with one another and create an overlapping network map that
showcases how information and ideologies spread through groups of people. This quality of
networks being dynamic and ever changing is extremely important in terms of how non-
profits perceive their own activist networks. Non-profit organizations have the ability to
change how their network participants interact, how close they feel to one another and how
much they are able to engage one another. In addition to the ability to create strong and loose
networks, non-profits also have different network models to choose from to help achieve
video spreadability. There is no one specific network model that leads to video spreadability
perfection, but, rather, many different network characteristics that influence the dissemination
of video information. Below are examples of network model characteristics that help
determine how likely content is to spread online.
While networks are often measured by size, this is merely the first step in the basic
analysis and comparison of networks. Comparisons of network sizes can start most basically
with analyzing the number of nodes, or people, within a network. Analyzing size can give one
a baseline number to compare expansion against and to use to establish goals. For example,
expanding the size of a network from 1,000 to 1,100 in the first quarter is a way of
establishing a benchmark and goal for future network analysis.
The size of a network can also be determined by secondary and tertiary network
connections. This is a more advanced way to measure network size that relies not only on the
people who are directly connected with a cause or organization but also on the nodes to which
each primary connection is connected. This can show analysts a larger view of the network
and help them analyze the capacity under which content is shared as the network expands. For
example, knowing the number of people who “like” an organization’s page on Facebook

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gives one a baseline for the primary nodes in that organization’s Facebook network. However,
knowing to whom each of those people is connected confers the ability to study secondary
connections and opinion leaders within a network. Having the ability to analyze multiple
layers of a network is important for tracking how a video spreads through the overall network.
Another way networks are often characterized is by the number of weak or strong ties
within a network. A weak network tie is a tie that is easily broken, while a strong network tie
is a reliable connection that will likely pass information along. While the author has discussed
the power of having a larger network, size is not always as important as network strength. For
example, two networks may contain the same number of people—1,000 people—but the
organization with the loose (weak) network may find it harder to engage its network. On the
other hand, a tight (strong) network is extremely connected to its information or organization
and therefore more likely to share or spread information related to the network.
With the recent rise in social media use, network strength is particularly important.
There has been a relatively high emphasis placed on collecting the most followers possible on
Twitter or the most fans on Facebook; however, this trend may, in fact, lead to loose
networks. When organizations buy likes or followers, those followers are likely to be
disengaged and therefore not likely to want to expand social capital to help spread the
message of a cause. Designating a network as loose or tight is very important in assessing the
likelihood of spreadability.
Networks can also vary by how much reciprocity there is among members. For
example, reciprocity in a network of Twitter followers is determined by how likely supporters
are to communicate not only with the cause itself but also with others within the network.
This is an important distinction because higher levels of member-to-member reciprocity mean

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more engagement with the content and, therefore, more likelihood of having a tighter
network.
Engagement reciprocity can be measured by how active a member of a network is
with original content and how often he or she shares or comments on the original content.
This is one of the most common forms of SNA measurement, as sites like Facebook now
monitor engagement reciprocity for every page. Member-to-member reciprocity can be
measured by how likely a follower is to engage in communication with another follower and
create a true dialogue. Because of privacy settings and restrictions, member-to-member
reciprocity is more difficult for most organizations to monitor. While it takes strategy and
time to develop a truly reciprocal network, achieving both forms of reciprocity is the crux of
developing a network that is ready to spread video content.

Factor Three: Distribution
A video without a distribution mechanism is simply an online video waiting for people
to access it. Instead of waiting for views, we can help guide traffic and increase spreadability
by creating a targeted distribution strategy for success. Distribution strategies can vary by
budget, accessibility and technological needs. Here, the author explores some of the most
common ways to increase the spreadability of a video after it has been created and uploaded.
Distribution of online video content is divided into push and pull tactics. Pull tactics, such as
search engine optimization and search function tagging features, help attract an audience to
content. Push tactics help push content to an audience; they include tactics like social media
posts and traditional print media.

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The first step in distribution is understanding and shaping the distribution based on the
networking analysis found in factor two. For example, if an organization’s network
characteristics and analysis show that the network is highly engaged via email but is not
engaged via social media, the organization must change its distribution channels to cater to
the existing audience needs. Additionally, if network analysis demonstrates that the network
is not active at all, spending time to build a network may be the first step toward achieving
success. The following are a variety of the basic ways that non-profits and causes distribute
video content:
• E-newsletters
• Social media platforms
• Email
• Websites
• Partnerships and sponsors
• Traditional and print media

While it seems easy to push content on some or all of these platforms, each platform has
specific needs and associated strategies for success. Simply placing content on a platform
does not guarantee that followers will see, let alone care, about the content being directed at
them. Instead, creating a cohesive and strategic plan will help target key opinion leaders and
supporters to ignite the spread of content. While sending e-newsletters can help a non-profit
spread its word to current supporters, understanding the open rate of those e-newsletters and
the click-through rate of the links contained within helps determine if this tactic indeed
spreads media. For example, if a newsletter is sent to 10,000 people but only 1,000 of them
open the newsletter and only 10% of those people click on the content, it may be easier to
spread the same content to 100 people on Facebook than to add it to a newsletter.
Therefore, understanding a non-profit organization’s content exposure and distribution
channel metrics will help the organization facilitate the rapid spread of video content. While

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most suggested distribution methods depend on pushing content to current networks, some
distribution relies on pulling supporters toward content as well. Pull distribution strategies
have recently been gaining importance because of the value of search functions (Ross, 2007).
Think about how most people find information in the business of daily life: they use the
Internet to search for what they want to know (Pooja et al, 2013). For example, if a person
wants to bake cookies but does not have a recipe, he or she would commonly use a search
engine like Google or Bing to find a cookie recipe. The keywords he or she types into the
search engine could be terms like cookie, recipe or cookie recipe. Each way the words are
written changes the information that is displayed. It is our job as public relations practitioners
to make sure we tag content correctly so that it is displayed as early as possible during web
searches. These nuanced details are the difference between video content that is easily found
and content that is hidden in the abyss of the Internet.
Achieving a higher place in keyword searches means that content can be more easily
found by those that seek it out via search engines. This is an important characteristic of
spreadable content because looking for content requires additional time and, therefore, those
who seek content should be able to find it in a quick and immediate way.
Most online video distribution channels push out content in terms of push-pull marketing
tactics. However, experts say that relying solely on push content may not be advisable (Urban,
2005). Instead, creating buzz and anticipation before the release of a video combines push and
pull tactics, bringing supporters directly to the video. For example, if a video is in the news
before it is even released, people are more likely to search for it or seek it out on their own.
Creating enough buzz and attention to generate a pull factor is important because it allows
multiple marketing approaches to be used on the same video. Creating hype before an online

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video launch has become a popular line of approach to try. PETA’s 2014 Super Bowl
advertisement was able to pull people into its online video content because it was never even
a Super Bowl ad. The organization utilized the publicity of the Super Bowl to create a fake
advertisement to release on YouTube. This stunt was able to draw millions of organic views
to the video using a combination of push and pull tactics. Therefore, using both tactics helps
spread resources and gives organizations the ability to not rely on merely one factor to
distribute their content.
The factors involved in creating spreadable video content—creating the content (factor
one), understanding networks (factor two) and creating distribution strategies (factor three)—
shape the basic model for achieving success with video content online. However, why exactly
is spreadable video content so vital for non-profits and causes?

Videos Have The Ability To Create Change
Videos are so vital because their visual and emotional elements have the ability to
draw in supporters, to spread ideas throughout the Internet and to truly inspire and create
change. A minimalistic metric, the number of views a video receives, provides a broad
generalization about how a video spreads through a social network. The amount of times
people repost, share or comment on a video increases engagement and gives analysts the
ability to track how the video travels through social networks. Nahon and Hemsley provide a
definition for video virality:
“A social information flow process where many people simultaneously
forward a specific information item, over a short period of time, within their social
networks, and where the message spreads beyond their own social networks to

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different, often distant networks, resulting in a sharp acceleration in the number of
people who are exposed to the message.”
While virality may be an overarching goal that people want to achieve, marketers and
public relations practitioners have learned that the best way to fulfill virality is by creating
content that is spreadable. Jenkins discusses spreadability of media as the true goal when
producing online content (Jenkins, 2011). While the concept of virality concentrates on the
content itself creating buzz, spreadability goes a step further and makes the viewer an active
participant in the media. Jenkins, Ford and Green suggest that we should view audience
members as curators of information and concentrate on increasing their involvement.
Therefore, while virality is the term many strive for, spreadability is the way it is achieved.
KONY 2012, while controversial in its content, is an exemplary case of how a social good
video can spread through the Internet via a very strategic and networked approach.

YouTube As A Platform For Social Change: KONY 2012
To better understand what a successful campaign for social change is, the author turns
to the example of KONY 2012. Unpacking specific details of the campaign that spread
throughout the Internet like wildfire gives us the ability to understand what is possible for the
future of social change video campaigns and content. How did KONY 2012 achieve the feat
of 112 million Facebook reposts, response videos and shares in its first six days alone?
Invisible Children, the organization that created KONY 2012, employed the three factors
above to craft a well-planned and well-executed social good campaign.
KONY 2012 is a 29-minute video created by Invisible Children that tells the story of
how Ugandan warlord Joseph Kony came to power. It does this through the unique viewpoint

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of “making him famous.” Daley (2013) argues that videos like KONY 2012 surpass
viewership expectations because they are targeted toward digital natives: Millennials. He
explains that understanding Millennials helped the video’s creators focus on keeping the
attention of young people throughout the entire 30-minute YouTube video. Bright colors,
simple messaging and a targeted storyline created a sensational video that has been viewed by
more than 98 million people. The video sparked controversy, blogs posts, research papers and
dozens of spoof videos (Meikle, 2013; Harison, 2013). Harison explains that the “attention
effect” is a phenomenon in which a video’s popularity increases because of the multiplied
conversations happening simultaneously on social media, in traditional media and in person.
This trifecta of conversations made it possible to achieve the “attention effect” in the case of
KONY 2012. It did this by capitalizing on strategic network choices to create the ultimate
spreadable media platform.
The “attention effect” was attained in part because of an already-existing network of
engaged supporters and a video production team ready to create a viral documentary. The
three factors for creating spreadable media were not only achieved but perfected by Invisible
Children’s KONY 2012 campaign.
The KONY 2012 video achieved factor one, creation of great video content, by
crafting a professional storytelling video with a simple and straightforward message. The
video itself tells the story of Joseph Kony in a simply yet direct way. The resulting
documentary-style video encourages viewers to watch the entire thing because it draws on
drama and emotions like anticipation. The theatrical and high-quality video provides a great
base for building emotional appeal on top of the existing content. Regardless of the
professional-quality shots, the video’s ultimate call to action is to spread the message about

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Kony. Therefore, the more people who watch the video, the more advocates and supporters
there ultimately are to spread the video.
Factor two, network strategy, is where KONY 2012 surpassed expectations and set a
new precedent for creating viral social change video networks. Long before the release of the
KONY 2012 video, Invisible Children’s network was being created in order to help spread
content. The network is comprised of strong ties, some of which link to other networks,
helping to bridge them. This combination of strong ties and bridge links creates a network
ripe for spreading media. Invisible Children’s network started with 54,000 Twitter followers,
a majority of which fell into its target age demographic of 13-25 year-olds, before KONY
2012 was even released (Tunhiem, 2013). In addition, the non-profit also had key influential
opinion leaders following its social media. The organizers asked influencers like Ryan
Seacrest, Bill Gates and Katie Couric to retweet the KONY 2012 video. This triggered an
immediate spread of the video content that reached millions of people through just a few key
connections. In the ultimate use of network theory, Invisible Children created and published a
list of influential celebrities whom the organization then asked its network to contact in hopes
of spreading KONY 2012. Therefore, Invisible Children was able to utilize its existing strong
network ties to reach celebrities with whom the organization had had little connection
originally. From there, the video was able to spread through networks across the globe.
KONY 2012 also exceeded expectations for factor three, video distribution, through
the use of a thorough and strategic media release strategy. After targeting opinion leaders and
influencers, Invisible Children strategized ways to gain exposure to other audiences. A
comprehensive radio and television media plan helped create and gain exposure for the video

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in the traditional media realm. This strategy gave it the “attention effect” trifecta of
traditional, online and word-of-mouth exposure.
Overall, the KONY 2012 video campaign is helpful to PR practitioners because it
demonstrates that having a strategic plan for all three factors—video creation, network and
distribution—leads to the ability to create spreadable media.

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CHAPTER 3: METHODS
To better understand the different ways causes and organizations are currently trying
to create spreadable media, the author combines expert interviews, case studies and network
analysis to form a broad idea of the existing landscape. The combination of interviews and
primary and secondary research helps to better inform the analysis within the case studies.
After conducting each of the interviews, the author chose four non-profit organizations
that have locally affiliated branches in Los Angeles for the case studies. The non-profit
organizations are also each unique in network size, network strength and digital strategy.
After all the non-profits were chosen, digital metrics were recorded on their social media
platforms from December 2013. In an effort to utilize both quantitative and qualitative data, a
combination of network graphing, content analysis and search engine optimization keyword
tagging data was recorded.
The author interviewed three experts, each specializing in a different factor in creating
spreadable media. Dan Neri, the owner of Matter, specializes in creating media and
advertisements for social good campaigns. Neri’s expertise lies in factor one, content created,
and factor two, social good networks. The author also interviewed Will Dekrey, a manager of
networks with a Washington D.C.-based consultancy. He shed light on the intricacies of
networks and stressed the importance of understanding the value of unique networks. The
third interviewee was Joe Nolan, the head of social media for StubHub. Nolan’s expertise is in
distributing content via social media and engaging users to become true advocates. The three
interviews inform the case studies and the tips for creating spreadable media.
Overall, the purpose of the case study methodology is to better understand how
different types of networks use video content to create spreadable media. There is no black-

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and-white equation to follow to create engaging, spreadable social media, only a spectrum of
different strategies. By using the case study methodology, we are able to better understand a
few different ways current and innovative non-profits are using video content and distribution
strategy to create media that is likely to spread.

Understanding Factor One: Content
To better understand and measure the content creation techniques of non-profits, the
author utilized a combination of interviews and content analysis. The content analysis was
conducted on YouTube videos uploaded by each non-profit. Six videos from each non-profit
were analyzed: the three with the highest viewership count and the three with the lowest
viewership count to ensure no viewership bias.
The metrics, emotional appeal and length of each non-profit video were recorded.
Metrics and length were recorded for the full duration of the videos, excluding
advertisements. The emotional aspects assigned to each video were recorded by one coder
from the primary emotions as identified by Plutchik, a primary emotional appeals theorist
(Plutchik, 1980). The primary emotion recorded was the emotion seen for most of the video,
while the secondary emotion was the emotion less evident in the video. If high levels of
emotions were not evident, no emotion was recorded. The coder characterized a video as
having a “high level of emotion” when an emotion was seen for over half of the video.
The quality of the videos was also scored on a scale from one to ten, one signifying low-
quality movies with low resolution and ten meaning high- and professional-quality videos.
While no statistical correlations are mapped from this content analysis, an overview of

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emotions and length can help determine possible patterns that are associated with videos that
have more spreadability.

Understanding Factor Two: Networks
The author used MentionMapp to map each non-profit’s Twitter network.
MentionMapp lets people map networks without needing to understand coding, demonstrating
that insightful network information can be accessed without extensive study. With simply an
organization’s Twitter handle plugged into MentionMapp, the computer program can generate
and map the handles and hashtags the organization uses most often. It then creates a network
map of influence to show how the organization can better utilize its existing networks to
spread media and content.
The Twitter handle in the middle of a MentionMapp is the account on which the map
is based. All of the surrounding handles and hashtags then branch from the main account.
Quality of relationships such as “strong” and “weak” is determined by the number of times
accounts retweet each other or reciprocate information.

Understanding Factor Three: Distribution
To understand how organizations are currently distributing videos and what
techniques are being used, the author drew on social media metrics to understand the push
factors involved in distribution and on search engine optimization and tagging measures to
understand pull factors.
The search engine optimization (SEO) metrics were determined by the keyword
density on each YouTube video’s page. The keyword density was found by using

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tools.seobook.com/general/keyword-density/. Understanding keyword density in relation to
SEO tagging helps people better determine if videos and content are being properly tagged.

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CHAPTER 4: CASE STUDIES
CASE STUDY 1: CHILDREN’S HOSPITAL LOS ANGELES
Children’s Hospital Los Angeles (CHLA) is a world-renowned facility with a mission
to create hope and build healthier futures. The hospital has been ranked the Best Children’s
Hospital by US News for the past five years in a row. The doctors, researchers and staff are
widely praised on social and traditional media. A combination of its high acclaim and
rankings and a location in the heart of Los Angeles has brought CHLA a mixture of celebrity
visits and important research. Overall, CHLA’s social media presence is robust and active.
With over 17,000 Twitter followers and 25,000 Facebook fans, Children’s Hospital updates
its sites daily, and it is most active on Twitter. Most of the social media content is related to
news updates, success stories and ways to become involved.

Factor One: Content
Children’s Hospital Los Angeles produces hundreds of videos, with some receiving
less than 100 views and some receiving millions. After analyzing the most and least viewed
YouTube videos on the CHLA page, the author offers a few descriptive qualities to help
explain its branding and audience engagement. First, video quality does not account for spikes
or dips in video viewership or engagement. The content analysis of the most and least viewed
videos did not show a connection between video quality and amount of views. In fact, two of
the most viewed videos received a rating of three out of ten for video quality. Videos with low
resolutions and even without the proper YouTube dimensions were viewed quite often in
comparison to the professional-quality videos. After further examination of this trend, the
actual correlation becomes clearer. Videos with low resolutions are created by everyday

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patients and have the power to make viewers feel closer to patients and families than
professional-looking videos. Their homey and raw qualities have skyrocketed most patient
videos to being the most popular videos as well.
In addition, the videos with the most views have a few other shared qualities. The
videos that received high engagement are short in nature (less than three minutes long) and
use emotions from opposite sides of Plutchik’s eight primary emotions. The combination of
short, easily digestible videos and a heightened emotional state created a good starting point
for the videos to receive engagement.
While the types of emotions found in the most viewed CHLA YouTube videos differ
across the spectrum, what they have in common is that divergent emotions, or emotions on
different sides of Plutchik’s wheel, are used in combination. The top videos display emotions
such as joy (primary emotion) and surprise (secondary emotion) from different sides of the
spectrum. Therefore, utilizing divergent emotions helps build a stronger connection with the
viewer. This is also supported by Berger and Milkman’s virality research, which
demonstrated that multiple strong emotional ties elicit the highest amount of content views.
Within the course of a thirty second patient-made video, the viewer is able to experience a
range of emotions coupled with a direct connection to the patient or patient’s family.
Some Children’s Hospital Los Angeles videos are viewed quite regularly, while others
are not. There are hundreds of videos on the Children’s YouTube page, but most have
relatively low engagement, with less than 1% of subscribers commenting on the videos and
most receiving less than 1,000 views. Dan Neri, a marketing and advertising expert, reminds
us that each cause may have different objectives based on its goals. For example, Children’s
Hospital’s goal may be to increase viewership counts on videos, or it may want to engage

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existing viewers on a deeper level. By benchmarking and understanding each non-profit’s
strengths, we are best able to reach the most people within a desired network. Children’s
Hospital’s YouTube page has more regularly updated content and more engagement than it
did in previous years. Therefore, if increasing content or engagement are objectives for
CHLA, it is fulfilling these objectives.

Factor Two: Networks
Overall, CHLA’s social networks are targeted toward supporters of the CHLA
mission. Its social media offers a mix of posts about lifestyle improvement, hospital patient
success stories and event information, and the engagement per post is relatively high, with
most posts getting shares, likes and comments. Interestingly, the high engagement per post
comes from a high amount of “shares” of Facebook posts. Will Dekrey mentions Facebook
sharing as a crucial part of spreading content on social media. Dekrey describes sharing on
Facebook as vital to network expansion because it is the most public form of showing others
that one not only cares about a topic but that one also cares enough to share information about
it with one’s own network. The “share” button on Facebook is one of the best ways for an
organization to expand its social network. Sharing means that an organization’s followers
trust its brand enough to deem its information valuable and to push that information beyond
the existing network.
While CHLA’s Facebook page is updated in a fun-yet-formal tone, its corresponding
Twitter account is much more loose and friendly. Posting upwards of five to ten times a day,
the account uses graphics, emoticons and exclamation points. This friendly attitude is echoed
by retweets and responses, and the brand is viewed as an opinion leader for children’s health.

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While not many direct questions come via Twitter, the high retweet and mention rates echo
the findings on Facebook. Retweets are one of the best ways on Twitter to reach new
networks, as a retweet signifies a higher level of social capital than a mention or a direct
message.
The network map below shows CHLA’s current Twitter network. The orange
highlighted links are influential people and hashtags within the network. An interesting aspect
of CHLA’s Twitter network is that the most influential Twitter handles, or nodes, are those of
employees and influential leaders in the field of children’s medicine, therefore demonstrating
that the links that expand CHLA’s spreadability are health professionals and advocates. For
example, @MelaniewWong is a specialized public health professor at UCLA. As with many
of the other influential nodes, @MelaniewWong shares in the dialogue about Children’s
Hospital and specialized hospital care for children. Therefore, the opinion leaders within
Children’s Hospital’s social networks are people in the public health and advocacy space and
current and past patients of Children’s Hospital.
Another interesting differentiation in CHLA’s social network is the amount of
influential nodes, or people, there are within one bridge of CHLA. For example, CHLA is
directly connected to @MelanieWWong, who is a bridge, or linking node, to lots of
influential people, such as the NBA’s Pau Gasol. Therefore, @MelanieWWong is a
strategically important node because, when she spreads awareness, her tweets have the ability
to amplify a message throughout a new cluster of highly influential followers.
Interestingly, while many of CHLA’s videos highlight celebrity involvement within
the organization, none of the network’s designated opinion leaders are celebrities. This
demonstrates that while videos may become more popular when celebrities are involved, the

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audience still considers doctors and advocates to be the influencers.

Factor Three: Distribution
Children’s Hospital Los Angeles utilizes its YouTube channel and its social media
connections to distribute videos. It currently has 3,497 YouTube subscribers. A recent
YouTube study found that roughly 25% of YouTube subscribers become disengaged or their
accounts become no longer active within one year. Therefore, the combination of the high
drop-off rate and the already difficult retention rate of social media engagement makes
YouTube a difficult platform on which to measure strength via subscribers.

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While CHLA’s YouTube subscribership is strong, its biggest strength in numbers and
engagement is in its Twitter and Facebook networks. When a video is added to Facebook or
Twitter, it increases its spreadability to the thousands of followers who are already supporters
of the hospital. For example, the latest mention of a video, about Los Angeles Laker Pau
Gasol visiting the hospital, received more than 500 likes, which is more than double the
amount of likes any other content has received.
While CHLA’s network strength is its push tactics like Twitter and Facebook, its lack
of pull tactics, or ways that people find video content on the web, is a weakness. There are
multiple reasons for why it is difficult to search for video content about CHLA. First, there is
a television show called Children’s Hospital. There are also almost a dozen leading hospitals
around the world that have the words “Children’s” and “Hospital” in their names. Therefore,
keyword tagging lists a variety of content, some of which is not related to Children’s Hospital
Los Angeles. Additionally, its YouTube videos are named with generic words like “today”
and “story.” Utilizing key words about hospitals such as “patient” and geotagging the location
will help people who are searching to find the correct information. CHLA can improve its
keyword tagging and marketing features to increase its distribution range and the
spreadability of its media.
While there is a desire for all social change videos to receive the highest possible
amount of views, the Children’s Hospital Los Angeles YouTube channel is unique in nature.
The videos offered on the channel are partitioned to target two types of audiences. On the one
hand, the broad, general videos of patient successes are targeted toward possible CHLA
supporters, families and sponsors. On the other hand, some videos are very specific and
educational in nature. Interviews with doctors in specialized fields or “how-to” videos for at-

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home care are very specific but very helpful. These videos are not meant to “go viral” by
nature but rather to help a specific niche of patients. These videos directly help fulfill the
mission of Children’s Hospital and are very important despite their lack of content views.
Therefore, it is clear that not all videos need to be tailored to “go viral.” Focusing marketing
efforts on the content that is most applicable to large masses of viewers will give CHLA the
greatest chance for viral success.
The YouTube videos with the lowest viewership rates are those that concentrate on the
hospital and its staff and employees. While the videos lack the amount of emotion of the top
performing videos, they also specifically lack the story-telling features of the other videos.
While the top performing videos take the viewer through a condensed story, the least viewed
videos maintain the same monotone emotions throughout. Additionally, the least viewed
videos tend to be longer, some of them over four minutes. This again emphasizes that
Children’s Hospital Los Angeles’ audience prefers short, emotional and heartfelt YouTube
videos. Concentrating on the characteristics that already make CHLA’s top videos successful
will help motivate established viewers to share and repost videos on their own social media
pages and through email. This high level of social capital is an investment that expands the
network past its current followers and to new levels of possible supporters.
Understanding the video content and intended audience is the first step to building a
successful social change video. The next step comes from network analysis and understanding
network chains. While CHLA’s social network is relatively large in nature, its YouTube
Channel can more effectively grow its network through changing keywords and tagging.
Properly matching the pages’ main words with what will be entered into search
engines helps people outside of the established network easily search for videos or content.

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For example, the current Children’s Hospital Los Angeles YouTube channel is highly tagged
for words like child, children and ho (short for “hospital”). However, words that may more
accurately be associated with Children’s Hospital, such as “hospital,” “nurse” and “research,”
appear less than half the time. This distinction means that while the established CHLA
network may encounter a YouTube video through a Facebook status, Twitter post or the
“recommended” section on YouTube, it is difficult for people outside of the network to
appropriately search for and reach the desired content. Switching search engine keywords will
help CHLA’s content appear higher in search functionality.
After further review of the content, the author found that simple and easy keyword
tagging may make the YouTube videos more accessible in online searches. Words that are
bolded, underlined or italicized are often viewed as more important by search engines.
Additionally, titles of YouTube videos and the first sixty words of their descriptions are given
preferential treatment in the eyes of search engines.

Recommendations
Overall, the social media and YouTube analysis of Children’s Hospital Los Angeles
shows that its network is geared toward creating spreadable video content. The organization
utilizes its intertwined network and partitioned audiences, gaining a high engagement rate
with supporters. The author recommends that CHLA alter its YouTube video tagging to better
reflect keywords associated with the hospital. Adding keywords such as “children,”
“hospital,” “sick” or “patient” as much as possible will help CHLA move up in searches.
Additionally, creating targeted keywords will help videos align with the correct audience.

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Non-profits and organizations with relatively strong, interconnected networks and
high engagement rates may begin to think about expanding their networks beyond what is
established. To expand a network to include meaningful and relevant audiences, begin by
adding keyword tagging and detailed title references to videos. This difference will increase
the likelihood of content being brought to the top of searches, resulting in more YouTube hits,
therefore expanding a network. Properly tagged videos will also help people discover
recommend related videos and content about the organization.

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CASE STUDY 2: MAKE-A-WISH
Make-A-Wish International began in 1980 when a group of people helped a little boy
fulfill his wish of becoming a police officer. After the success of that one case, the non-profit
was created to fulfill the wishes of terminally ill children. To date, the organization has helped
fulfill over 300,000 wishes with the help of 30,000 volunteers. The non-profit has now grown
into a chapter-based model, with Make-A-Wish chapters set up across the globe. To date,
there are 62 chapters across the United States. On a national level, the organization boasts
more than half a million Facebook fans and 150,000 Twitter followers. Most recently, Make-
A-Wish received a great deal of attention regarding the Bat Kid stunt, in which the
organization transformed San Francisco into Gotham City and Miles, “Bat Kid,” was able to
save the day. This event alone garnered almost half a million tweets and 1.7 billion mentions
on social and traditional media (Taylor, 2013).

Factor One: Content
The most viewed videos on the Make-A-Wish YouTube channel are those about kids
who have received wishes. Not surprisingly, these videos are heartfelt and emotional. Unlike
in the case of Children’s Hospital Los Angeles, Make-A-Wish’s videos that are viewed often
are a bit longer, averaging about three minutes. Some videos on its channel are upwards of ten
minutes long, making the three-minute videos short for the Make-A-Wish channel.
The top three most viewed videos on the Make-A-Wish Channel do not share
similarities in terms of video quality. Much like in the Children’s Hospital Los Angeles case
study, video quality does not correspond to the number of times something is viewed. The
videos that were shot on phones or flip cameras have the ability to become just as popular as

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videos made with professional video production equipment. Dan Neri, an advertising and
marketing expert, explains the reason for this phenomenon by emphasizing that it is the
emotional appeal and storytelling features that connect the viewer to the video—in other
words, good storytelling is key to creating any video, cause-related or not. The same theory
from the CHLA case applies to the Make-A-Wish case. Because their contents are based
around terminally ill children, videos shot through the eyes of children or their families are
not held to the same standards as professionally-shot footage. The footage feels more
endearing and heartfelt when the video is not professionally edited. While the Make-A-Wish
channel has videos that are promotional in nature, most do not promote the organization as a
whole but rather celebrate individual stories of kids.
Videos told through the perspectives of children are extremely popular on the Make-
A-Wish YouTube channel, topping the lists of the most commented and most shared footage.
Not surprisingly, the most viewed videos feature a child’s story in addition to a celebrity. The
combination of a storytelling feature with emotion and celebrity status helps certain videos
rise above others in terms of comments, likes and viewership. One of the most popular videos,
in which a child meets Kobe Bryant, has been viewed over 500,000 times and has roughly
5,000 comments and likes combined. While 1% engagement (measured by the amount of
people who comment on or like a video compared to the amount who view it) may seem low,
it is not abnormal for many videos, particularly those of social good campaigns (Kaplan,
2010).

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Factor Two: Networks
To better understand the Make-A-Wish network, the author analyzed the Twitter
network of Make-A-Wish America, the broader Make-A-Wish organization.

As one can see from the graphic above, the types of influencers in Make-A-Wish’s
network are very different from those seen in the Children’s Hospital Los Angeles case study.
The influential Twitter handles are celebrities, such as those involved in the NBA, and local
branches of Make-A-Wish. Because of the high reciprocity rates (based on mutual likes,
comments and shares) between the local branches and the Make-A-Wish America brand,

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some of the best brand advocates for Make-A-Wish are actually within its own network.
These people become the strongest links within the organization, and each chapter becomes
its own cluster of influence within the overall Make-A-Wish brand. Some of the largest
supporters are smaller Make-A-Wish branches using hashtags like #WishNation and
#ShareUKBabWishes. Both of these hashtags are parts of larger campaigns from different
branches of Make-A-Wish.
The intertwined and supportive nature of Make-A-Wish suggests that it already has a
close-knit network that is ready to help spread video content. Like the KONY 2012 network,
the Make-A-Wish network includes connections to local chapters and celebrities that support
its cause. Therefore, this network is advanced in nature and has the ability to spread media
quickly through its system of supporters.
Before one understands how to help engage the established network, one must
understand why certain videos are becoming successful and others are not. For example, a
video highlighting Make-A-Wish’s partnership with Southwest Airlines received very few
views. While the airline co-promoted the content, the video itself does not link to other similar
content and does not encourage engagement. The videos content on the sidebar include a
mixture of videos about Southwest Airlines, other initiatives and new Southwest policies.
Therefore, the video content is not easily found, as there are few related videos in the same
genre. Furthermore, if someone were to stumble upon the video, the mixed content in the
sidebar may or may not lead him or her to another Make-A-Wish video.
Overall, this network seems ready and primed for spreading content. With a few
exceptions like the Southwest Airlines partnership, most of its partnerships (such as with
NBA Cares) seem to be featured well on social media, with cohesive network exchange in the

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social networking map. Starting with such a high rate of engagement and network exposure,
how can we create videos that are as spreadable as possible? A large portion of spreadability
is established through distribution channels, of which Make-A-Wish has many.

Factor Three: Distribution
Make-A-Wish excels in push marketing distribution, with Facebook and Twitter pages
that are updated often and high engagement with current stakeholders through comments and
shares. As Joe Nolan discussed, the audience’s willingness to engage with information
through likes and shares helps Make-A-Wish increase exposure to new audiences and
continue to grow. Some interesting push distribution behaviors separate Make-A-Wish from
the other case studies. Almost every network post is accompanied by a picture of Make-A-
Wish kids. This picture content increases spreadability as more imagery content makes access
across media platform types (computer, mobile, tablet) easier to grasp. The very high
engagement rate suggests that, like in the Children’s Hospital Los Angeles case study, Make-
A-Wish’s Facebook content is indeed driving an actively large network. The way by which
the organization manages its Facebook presence adds to its existing brand and helps grow
donor and volunteer support. Posting once or twice a day helps turnover new content without
overwhelming the active Make-A-Wish followers.
The Make-A-Wish Twitter stream is run a bit differently than the Facebook feed.
Make-A-Wish posts on Twitter upwards of four times a day, usually posting people’s wishes
and pictures. While it is rare for Make-A-Wish to retweet people on its Twitter stream, it is
actively responding to people on Facebook. This difference speaks to the unique
communication styles of Facebook and Twitter. Make-A-Wish most likely responds to

46

questions and comments on Twitter via direct message instead of the public Twitter stream,
keeping personal information as private as possible. With roughly 150,000 followers and a
high retweet rate of 10 to 100 retweets per post, Make-A-Wish uses Twitter as a very active
and engaging form of social media. With both an active Twitter account and an active
Facebook page posting heartfelt and engaging content, what possible future issues are visible
in Make-A-Wish’s social media networking?
Because of the nature of Make-A-Wish, the segmentation between the national
organization and the local branches could cause confusion and clashes if strategies are not
aligned. There are over sixty local Make-A-Wish chapters, some with their own Facebook and
Twitter pages. This could then be where confusion and audience segmentation lies. While
Make-A-Wish wants people to be directly involved with their local chapters, it is also
important that they are aware of what the Make-A-Wish Foundation as a whole is doing.
Therefore, the Make-A-Wish case study concentrates on how to utilize the non-profit’s
growing network to build YouTube video support in the local branches and the overall
organization.
Most local Make-A-Wish chapters have their own YouTube accounts. They originally
post from their local accounts and the Make-A-Wish America account then chooses a few
videos to add to a playlist of videos from the local branches. The Make-A-Wish America
account has over 14,000 subscribers with a wide flux of video content viewing. The YouTube
account is run with different sections, including videos from the Wish List, videos from
families and videos from supports. These distinctions helps categorize and organize the local
chapter videos within the overall Make-A-Wish America brand. While this has helped
organize and brand the videos to keep content local in nature but professional in style, it also

47

segments the audience, making it more difficult for videos to gain the most reach. If our goal
is to create the best parameters to get the most spreadability for videos, how can we utilize the
existing, segmented Make-A-Wish network to spread video content?
All videos on the Make-A-Wish page have relatively high engagement rates, whether
they are viewed often or not. Therefore, the contents and storylines of the videos do engage
people once they watch, but the issue is rather a matter of trying to bring more videos higher
levels of viewership.
Another interesting characteristic of the YouTube channel for Make-A-Wish is that,
unlike other non-profits for whom content creation can be problematic, Make-A-Wish
America has video content to spare. With 148 original videos and videos still being uploaded
from before the channel existed, the Make-A-Wish channel is experiencing a flood of new
content. While these videos are being watched often, the abundance of videos on the site may
actually be diluting the message of Make-A-Wish. For example, the new promotional video
for Make-A-Wish, called “The Arc of a Journey,” was created by Make-A-Wish to give an
overall view of what the non-profit does. While the video has been live for almost a year, it
has received fewer than 30,000 views and only 30 likes. Comparatively, videos of kids’
stories usually receive many more views and higher engagement rates.
To help analyze how to best strategize selected videos on the YouTube channel of
Make-A-Wish, the author first turns to keyword analysis. The keyword search features of
Make-A-Wish videos and specifically the “Arc of a Journey” video are currently working to
bring people to the page. The keyword “Make A Wish America” has a density of 7% while
individual words like “wish” are also quite high. Therefore, people who search via search
engines or on YouTube as a whole should be able to easily find the tagged videos.

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The next factor to understand is whether the video follows the same emotional
composition as the other Make-A-Wish videos. Here, the author detects a vast difference
between the current branding of the promotional video and the other Make-A-Wish videos.
The branded promotional video uses only words and a white background to inspire the
message of helping terminally ill children. Conversely, most other videos on the channel are
bright, colorful and feature children in the main storyline. Therefore, the content of the video
itself may hinder its potential to go viral. Instead, videos with content similar to that of the
most viewed videos are possibly better equipped to gain followers, as followers are already
familiar with and like this content type.
Additionally, one of the most important features of YouTube is that it allows followers
and supporters to feel engaged with the material in a way that photos and words cannot
express. Our goal as PR practitioners is to make sure content demonstrates the emotions and
storytelling features that videos are best known for capturing.

Recommendations
After evaluating the Make-A-Wish social media channels, the author believes that its
Facebook and Twitter streams are aligned well for its audience and platform and that most of
the YouTube videos are also segmented well. However, a few small changes may create an
environment for easy video sharing and tagging across local chapters. First, the author
suggests tagging each video with the names of the child, celebrity and city that appear. These
features of the network are not fully utilized and can help people who may not know about
Make-A-Wish to find it via another aspect they connect with: the celebrity, the city or the
child. The goal of the segmented channels is to funnel important and interesting video content

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to the main channel as a means of drawing attention back to the local branches. This strategy
will help the smaller channels and main channel work together instead of competing for
content, which is what is currently occurring.
Make-A-Wish (and its YouTube channel) is an example of an umbrella organization
with smaller local chapters. Many non-profits are run with this model, such as Boys and Girls
Club, Girl Scouts and others. While it can be easy to create an environment in which videos
are competing for attention from the same audience, allowing the local branches to post and
then the umbrella organization to repost specific content will help keep the content fresh and
working cohesively.

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CASE STUDY 3: PEOPLE FOR THE ETHICAL TREATMENT OF ANIMALS
(PETA)
People for the Ethical Treatment of Animals (PETA) is one of the largest and most
well-known animal rights groups. PETA works on advocating for the proper treatment of
animals in many areas, including in the entertainment industry, the clothing industry and
research. The organization works through public education, investigation, legalization and
rescuing to bring light to the public treatment of animals. PETA is also viewed as a
controversial organization due to allegations of it scandalous activism efforts like throwing
paint and publicly protesting. PETA was founded in 1980 with the intention of bringing
animal rights issues to light.

Factor One: Content
The videos on the PETA page are controversial because of their graphics and content.
How can PETA best utilize controversy without diluting the message of protecting animals?
To better understand this, the author looks at PETA’s three most viewed and least viewed
videos. Is this approach different than in the above cases? Unlike the videos in the previous
case studies, PETA’s most viewed videos are professional-quality. The videos resemble
public service announcements: very quick segments with extreme emotions and professional
quality. All videos are less than ninety seconds, with the top three videos being less than sixty
seconds. However, time is not a factor that influences viewership rates. The least viewed
videos are also short in nature. Therefore, a different characteristic is separating the most
viewed and least viewed videos. To better understand what is separating the videos, the author
analyzed the emotions found within the PETA videos.

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Most of PETA’s videos are extremely emotional and graphic in nature. The top three
videos use the opposite emotion spectrum that was found in the CHLA videos. This means the
emotions displayed are very different and combine emotions like disgust and sadness or
sadness and surprise. The combination of very unlikely emotions helps the videos elicit strong
emotional connections from viewers, telling a small story within the sixty seconds.
The most viewed videos also highlight controversy and use celebrity influence. The
most viewed video utilizes a model to demonstrate why it is important to go vegan. This video
is controversial because of the implicit double meanings throughout. The same idea is also
seen in the third most viewed video, in which Jenna Jameson explains why she believes
people must stop wearing fur. Both videos have not only engaging content but also interesting
titles. “Too Much Sex For Jenna Jameson?” helps the video stand out on its own and grab a
unique audience. Interestingly, while one may think that the title and video footage take away
from keyword tagging, words such as “PETA,” “animals” and “animal ethics” are still
properly tagged with a density rate of almost 5%. The combination of controversial title,
interesting video content and tagged footage has helped this video be viewed more than two
million times. Another interesting quality to the video is that it is so controversial that the
viewer’s age needs to be confirmed before it can be watched. While one may suspect that this
would limit the amount of times the video is watched, the warning message (added by
YouTube, not PETA) makes the content more desirable. Two of the top three videos have
associated warning labels, which intrigue people and make them want to continue watching.
PETA’s other very popular video is a sad, very graphic video of the fur trade and
animal killing in China. The immediate graphic images are both disturbing and surprising in
nature because the viewer may not be expecting the sudden graphic content. While the video

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has not received a high engagement rate in comparison to other videos, the view count has
reached over three million unique views. As past researchers have also suggested, people are
unsure what to say about, or whether it is appropriate to “like,” videos that are sad in nature
but are more likely to comment on or “like” happy content. While the engagement rate may
indeed be low, the viewership rate manages to fulfill the mission of video—to spread
awareness about the animal fur trade.
After reviewing multiple videos on the PETA page, the author can say that there is a
target and storyline in every video. Neri suggests that this storytelling process is what
encourages people to watch content from start to finish. Creating short, impactful and edgy
messages is not enough; videos must also carry an interesting storyline to become truly
successful. While Make-A-Wish and CHLA are able to create joyous and happy content,
PETA takes the approach of targeting an enemy in every video. While the enemy changes per
message, such as against the fur traders, animal abusers or animal researchers, it remains clear
that in-group dynamics create an environment in which targeting an enemy creates a solid
network of support.

Factor Two: Networks
PETA’s Twitter network is mapped below via MentionMapp. Unlike the past case
study subjects discussed, PETA’s network is mostly comprised of advocacy groups and other
non-profits. This is an interesting combination that shows the true power of the PETA brand,
as other advocacy groups admire PETA’s work and it acts a great influence. Other non-profits
and advocacy groups retweet and cite PETA as a leader in the field. This has led to PETA’s

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association with causes rather than individual people. Issues like food stamps, obesity, vegan
diets and Sea World are connected to the PETA network.
While there is not one correct type of network that predicts spreadability of media,
these network characteristics show a very high likelihood of spreading content. The reason
PETA’s network is so different is its connection to other very recognizable brands and causes.
With such a large and influential following, PETA has a constantly-increasing ability to grow
its network.

PETA’s Twitter account demonstrates a tight and strong network of supporters and
advocacy groups. PETA is connected to many influential non-profits clustered by social good
causes. It is here that PETA exemplifies reciprocity, often retweeting content from other

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causes and in turn receiving retweets from them and expanding its own network of followers
in the process. In addition to its reciprocity, PETA’s network is also unique in bridging or
linking nodes. For example, @Alice and @SpeacialKev’s Twitter clusters (in the top right
corner of the network map) are bridged together by multiple linking connections or nodes.
This shows that while PETA’s network is growing, it is also interconnected and strong. Its
ability to create spreadable content is only amplified by a strong base and its willingness to
often retweet and engage with content.
With quick, emotional videos and an engaged audience, PETA’s social media
accounts may be considered an exemplary social good case study. The videos with the lowest
viewership on the PETA YouTube account mention celebrities from niche markets. To grow
and utilize each celebrity presence to its full potential and to increase viewership rates, it may
be useful to pay for targeted Facebook advertising in the niche markets in which those
celebrities are famous. For example, Meg Myers is a songwriter with 10,000 Facebook
followers. Using Facebook ads to extend her YouTube video to her Facebook audience may
help bridge the gap between social media platforms, engage a new audience and expand the
network.

Factor Three: Distribution
PETA’s social networking sites are interesting in terms of how they handle
controversial topics. In an effort to segment children away from the graphic images it posts,
PETA created the peta2 brand aimed at kids under thirteen years old. This brand has its own
Facebook page, Twitter account and website, which features information that is less
controversial than that on the main PETA site. While these sites have interesting information,

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the following case study will solely concentrate on the main PETA-branded Facebook page,
Twitter account and YouTube channel.
The Facebook page for PETA is extremely engaging due to its controversial topics and
content, which are both engaging and express easy calls to action. Steps like “WATCH,”
“UPDATE,” “SHARE” and “CHALLENGE” help spark interest in the content. However,
another noteworthy aspect to the controversial ideas expressed on the Twitter and Facebook
pages is that the people who follow the organization are not always likely to agree. Unlike the
subject matter of the non-profits in the previous case studies, Make-A-Wish and CHLA,
PETA’s topics are both diverse and controversial. This environment creates a network of
people who are more willing than usual to express opinions to their networks and confront
others about their opinions. PETA itself rarely comments on videos or questions, but does
repost others’ content. For example, other non-profits such as meat.org and various rescue
sanctuaries work together with PETA. Acts of mutual posts and collaboration help PETA’s
message become more mainstream to other audiences and help it expand its growth and
network reach.
People who do not support PETA may view its videos and pictures as controversial,
and they are more likely to follow or watch media that is presented from multiple sources.
Therefore, much of PETA’s social media presence strategy is to understand how to present its
messages in a meaningful and direct way without creating enemies.
PETA’s Facebook page is very active, with posts appearing multiple times per day.
While one my think that constant posting may be too much for PETA followers, it indeed is
not. Each post receives very high engagement rates, with some posts receiving thousands of
likes, comments and shares. Members of the PETA audience are devoted to the material and

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content and interact often with each other and PETA. Each of PETA’s posts is labeled with an
action before the main words. These actions then inspire people to do something and
participate instead of merely viewing the content. The activity helps expand PETA’s network
as people become more willing to engage with others and themselves. Some followers
become so engaged that side conversations and comments begin to bridge off from the
original material. For example, a PETA post from January 2014 sparked more than ninety
comments on one specific comment on the video. Upon further investigation into the
astounding engagement rates on PETA’s posts, the author discovered a characteristic that
increases in-group dynamics: almost all posts utilize a person, group or action as an enemy or
target. This allows viewers to become more involved because all the comments and thoughts
are against a proposed enemy, inciting extreme emotion.
The same level of emotion is exhibited on Twitter. Stories of extreme victories like a
recent ban on angora fur and very graphic, negative photos of animals constitute most of the
PETA Twitter feed. However, while the same amount of emotion is used, there are less
Twitter followers than Facebook followers. This difference is seen throughout most non-profit
organizations, as there are also more people using Facebook than Twitter. Overall, PETA’s
Twitter strategy of using images, tagged words and hashtagging has led to it having an active,
but less engaged, audience as well.

Recommendations
Overall, PETA’s YouTube channel is run and organized in a very unique way. The
professional quality of the page reads more as that of a company than a non-profit
organization. With 67,000 subscribers, PETA’s channel is very active and important for its

57

audience. The quality of the videos and channel is set by its profile page. While it seems to be
common for other non-profits to have a promotional video on their homepage, the PETA page
does not highlight one video or idea. Instead, videos are divided by cause. A viewer can click
on stories about Sea World, undercover stories or quick sixty-second info videos. The
segments utilize both interesting names and interesting videos, creating an engaging profile
page to start off the user experience.
Additionally, if a user stays on the PETA page, he or she will also see a pop-up icon
through which to support PETA through a donation or by following PETA’s other pages,
creating a digital strategy that seems to be consistent across platforms. Overall, the messages
and videos make the profile page efficient, easy to use and user friendly. Overall, PETA’s
social media presence and video usage exemplify the characteristics of a good social media
strategy in combination with network theory. Each platform is used for a specific purpose and
videos are kept short, professional and emotional.
PETA is an interesting example of a non-profit that uses controversy to its benefit in
terms of awareness and spreading its mission. While it may be easy to try to let moments of
controversy pass over us, PETA demonstrates that we can highlight these moments as
moments of success. Depending on the content and timing of the posts, organizations can
utilizing social media and videos to build an audience for organizations around a stated enemy
or villain may help increase awareness and improve storytelling features. As PETA
demonstrates, utilizing this tactic sparingly is effective and involves choosing specific events
and movements when strategy permits.

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CASE STUDY 4: GRADES OF GREEN
Grades of Green is an environmental education non-profit with a mission to inspire
and empower children to protect the environment. Launched in 2010, Grades of Green is a
start-up non-profit organization. As it continues to grow, so do its numbers: it now serves
more than 140,000 students in 33 states. With growing support, it now has the ability to grow
its social media numbers as well. Grades of Green currently has less than 5,000 total followers
on all social media platforms combined, but it has the ability to expand its reach and
influence; in other words, it has almost nowhere to go but up.

Factor One: Content
Unlike that of other non-profits, Grades of Green’s YouTube video content is very
diverse in both quality and length. Because middle and high school students produce most of
the videos, the length, quality and message often differs slightly depending on the student
who made the video. The content differentiation demonstrates the personalized quality of the
videos. While the different quality levels do not seem to affect viewership rates, the types of
videos do change the emotions and information presented. Some of the videos seem to be
informational in nature, telling people how to pack a trash-free lunch or how to switch to
making a trash-free lunch. Students seem to make most of these informational videos, and
while they lack emotion, they demonstrate a real side of the non-profit because they show real
students helping other students. Other videos are more promotional. They are of professional
quality and rate high in utilizing joy, whimsy and inspiration to draw in the audience.
While past case studies subjects saw success with a combination of primary and
secondary emotions, the Grades of Green videos differ dramatically in quality and emotional

59

context. While the emotions and quality do not seem to affect the amount of views a video
gets, none of the videos uploaded have received more than 1,500 views. Therefore, while the
view count remains relatively the same across displays of different emotions, this could be
because all video types have room for improvement.

Factor Two: Networks
Because Grades of Green is smaller and younger than any of the other causes studied,
it is understandable that its network may not yet be as robust theirs. How does a start-up non-
profit begin growing its network in a competitive networking environment? The graph below
shows the influential people and organizations within the Grades of Green Twitter network.
Interestingly, the way Grades of Green has developed a network is by becoming active
through established partners and sponsors. Subaru Pacific and Earth Friendly Products (Baby
Ecos) are brands with whom partnerships have been established. The network map
demonstrates that hyper local, green partners are most likely to be active supporters of Grades
of Green. While the network itself is small, the network hashtags and influencers are
concentrated in the green movement, a passionate and engaged sector of Twitter. The loose
network has the ability to grow by understanding how to reach influencers in that existing
network. The map below shows the local influence of Grades of Green’s reach and the
possibilities for improvement in strengthening existing links.

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Factor Three: Distribution
Grades of Green utilizes Facebook and Twitter to talk to its supporters. Both the
Facebook and Twitter pages have room for growth, with the organization currently having
2,000 Facebook followers and 800 Twitter followers. Before investigating the YouTube
channel, the author will assess its use of Facebook and Twitter. The Facebook page is updated
once every day or two, with stories from schools and information for the Grades of Green
audience. Interestingly, posts with pictures and stories from schools receive more attention
and engagement than interesting posts without pictures or personalized stories. The audience
seems to be more interested in hearing stories from Grades of Green schools; therefore,

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Grades of Green may be able to post more information about schools and programs and less
about general news. While eco-news is an important sub-segment, having at least one post per
day about a school or student at Grades of Green may create a more engaged audience. All
Facebook posts are directly sent to Twitter. However, because of the short character length of
Twitter, most of the automatically uploaded posts get cut short.
Grades of Green’s YouTube account is updated sporadically and has an active playlist
of favorite videos from other non-profits. Videos are posted when new content is available,
sometimes going as long as months between new posts. The YouTube videos receive from as
little as 100 views to as much as 800 views. While the videos lack high viewership counts, the
videos do garner high engagement rates of likes and comments. This suggests that, while not
many people watch the videos, those who do find the content engaging. How can Grades of
Green better distribute content to its audience? While the distribution channels of social media
are effective, Grades of Green also has the ability to rely on its expanding local network of
partners and sponsors. Creating reciprocal network relationships with partners and asking
them to retweet, repost or send out information can help Grades of Green spread video
content. Additionally, it may be more manageable and impactful to try to create the “attention
effect” noted in KONY 2012 by starting with these local partners in a specific area.

Recommendations
Before we concentrate on creating videos with the goal of spreadability, we must first
understand how to create spreadability on online social media posts. Spreadability means
understanding the platform differences between Facebook and Twitter and acting on the
differences in a way that enhances the network and creates high engagement rates.

62

The author suggests that Grades of Green establish an engaged network on one social
media site rather than try to post less often on multiple sites. Once Facebook and Twitter are
properly managed with a digital strategy unique to each platform, the author then suggests
tackling YouTube by regularly posting content. If a non-profit does not have enough new
content to post a video every few weeks or month, it might be best to keep efforts on
Facebook and Twitter until there is video content for YouTube. Once the non-profit begins to
have more content, it can then build out to have more social media presences.
Once YouTube is in full function, the author suggests Grades of Green create a sense
of organization within the channel itself. Dividing content into student-made videos and
professional videos will help it succeed and help people better understand the channel.
It may take time for new non-profits and causes to spread messages across newly
established networks. New networks are rather loose, and it takes time, reciprocity and
engagement to create strong ties and connections. While YouTube is a great platform on
which to spread a message, it requires time and attention to the platform. If a non-profit is
small and at the beginning stages of development, it may be easier for it to start with
Facebook and Twitter and then expand to different social media platforms when more
resources or time become available.

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CHAPTER 5: CONCLUSION
The four case studies above demonstrate different types of non-profit organizations
and the tactics they use to create spreadable media. While each case study shows that every
cause and situation is unique, the case studies also highlight a few lessons that can be applied
to the larger scope of cause-related videos. In fact, the case studies demonstrate that there are
best practices for each of the three factors that help create spreadable media.
The beginning stages of content development and creation, factor one, demonstrate
that some aspects of creating a “great video” are highly subjective. In the case studies, video
length ranged from fifteen seconds to many minutes long, and the videos’ viewing rates were
not dependent on the length of the video. However, while video length can change depending
on the cause and message, the videos that were viewed the most did share common emotional
appeals. As Berger and Milkman found, content with an emotional appeal or a call to action
was viewed the most often. While the content ranged in emotions such as joy, sadness, anger
or inspiration, it was the high level of emotional appeal that correlated to higher viewership
counts. Just as Dan Neri suggests, non-profits must find something to make their content
standout through a storytelling capacity. Therefore, while video length is subjective in terms
of spreadability, what is necessary to create spreadable media is an emotional appeal directed
at the target audience.
Factor two, network analysis, also showed commonalities in creating successful
spreadable media. Understanding network analysis and tapping into network nodes of high
influence can lead to bridges in new networks. Some people are more likely than others to
spark change, garner a new network or expand a network. These nodes contain, but are not
limited to, opinion leaders, groups of friends and supporters. Finding the people who can

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unlock an entirely new level of involvement can be the key to network expansion. Some of
the interviewees suggest singling out these opinion leaders. For example, after finding a list of
opinion leaders one would like to target, one should direct message or engage in conversation
with them. Letting opinion leaders know that they are important to expanding a cause helps
them take ownership and feel invested in the idea of watching it succeed. Following up
regularly and thanking them for sharing content helps continue a reciprocal relationship.
While the way each non-profit executes factor three, distribution of the content, is
different throughout different platforms, two key similarities remain: mixed marketing and the
spreadability mindset. All of the non-profits studied distribute video content on several social
media platforms and traditional platforms. While they differ across specific platforms, they all
utilize multiple methods of push tactics to get their videos out. This is an important
characteristic because they are not relying on one specific platform to create spreadability but
instead utilizing all overlapping networks to grow the “attention effect” for which social good
causes strive.
Throughout the presented case studies and the interviews another observation is clear:
spreadability is a mindset. Because spreadablity has so many components—keywords,
tagging, network theory, audience analysis and more—it is viewed as more of a mindset than
an objective. The objective factor will be measureable metrics that can help track the progress
of videos. However, to make truly spreadable content, one must always think about how to
make a video as user-friendly, simple and accessible as possible. While some may suggest
that the mindset of social media is to create posts and content that can attract likes, digital
strategist Joe Nolan suggests that it is more powerful to think of content in terms of
sharability and spreadability.

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While distribution usually consists of pull factors like social media, push factors like
search engine optimization and keyword tagging are also important. All case studies shared
the commonality that search engine optimization was crucial to making sure people were able
to view the content. In today’s world of search engines, optimized text and knowledgeable
media consumers, there are more and more people finding their own information online.
Therefore, it is our job to make sure this information is as easy to find as possible. All four
case studies prove that no matter how large the organization, proper tagging and SEO use is
still something that can be improved.
Videos have the innate ability to capture an audience, to make a viewer feel emotions
like nothing else and to compel people to act. We see this in Oscar-award winning films,
comical television shows and awe-inspiring documentaries. We can indeed feel the same
emotions through Internet videos. While YouTube may also house videos of babies and
kittens, it can be a platform for change, inspiration and advocacy.
Non-profit organizations and cause groups can harness the powerful medium of video
through inexpensive and amateur videography skills. By better understanding network theory
and knowing how to utilize networks, we can strategically create videos that will both appeal
to and communicate with our current audience. By maintaining and engaging with network
supporters, a non-profit can grow its network exponentially.
With a network mentality and the creativity of passionate do-gooders, cause videos
have the ability to reach far more people than they currently do. Utilizing the YouTube
platform in an effective and efficient manner can create spreadability to expand messages and
missions like never before.

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69

APPENDIX

APPENDIX 1: TOP 10 TIPS TO SPREAD MEDIA
Below are the top 10 compiled tips from the case studies, interviews and researched gathered.
1. Know Your Network Audience AND your target audience. Recognize that there may be
a difference, but that’s okay! Explain what the difference is
2. Know Your Goals and Objectives. Exactly how do you hope the video will create an
actionable response? Measure concrete metrics like how many people donate, how many
people sign-up or register to better understand the purpose for video content creation. By
doing so, we think beyond the numbers and more towards the actions.
3. Videos Are Not Mandatory. A great video content strategy takes dedicated time and
efforts. If your organization doesn’t have the dedicated time, think about starting small or
partnering to get the job done right.
4. Know Your Strengths. Create a storyline that plays into your strengths as a cause and
organization and mission.
5. Know Your Weaknesses. Analyze your social network and acknowledge where
improvements can be made. This will help determine if your objective is to grow your
network in size or capacity, which will in turn help guide your direction for video creation and
network strategy.
6. Keep it Direct, Short and Simple. The most successful videos seem to be 30-60 seconds
in length and leave the audience with a message of how they can help and an emotional
connection. Whether is be an emotion of anger, joy or disappointment, viewers must be left
with a feeling.

70

7. Don’t Become the Bland Brand. Take ownership of your brand’s personality and create a
stand-out image that helps you become known for something.
8. Go Beyond the Upload. Clicking the upload button is just the beginning of spreadable
content. It’s the time to implement network response, promotion and individualized platform
features.
9. Partner Up! Create engagement by creating more reciprocal relationships on Twitter and
Facebook. Utilizing tagging features and more personal shout-outs creating an environment
where people are more likely to share information.
10. Give a Reason. People are more likely to participate if they understand the reason behind
posting or sharing content. Instead of simply stating to “like” or “share” give a specific reason
of why you are trying to spread the word.

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APPENDIX 2: INTERVIEW QUESTIONAIRRE AND NOTES
While each interview was conducted in a conversational tone, the basic questions below were
used to facilitate the discussion. Additionally, while each interviewee specializes in an area of
network or viral spreadability, these questions began the discussion with all interviewees.
QUESTIONS:
1. Digital media is moving towards more image and video based content, what are your
thoughts when people or clients want a "viral video success?"

2. What characteristics do you think help YouTube videos go “viral?”

3. How often do you suggest companies and organizations to re-evaluate their digital
strategy?

4. What tactics do you use to share videos?

5. What do you measure besides video viewership?

6. What does video spreadability success look like to you or your clients?
Interview 1: Joe Nolan, Head of Digital Media at StubHub
1. Digital media is moving towards more image and video based content, what are your
thoughts when people or clients want a "viral video success?"
• There is not guarantee of a viral vide, but there are ways to increase likelihood
• Viral video success sounds like it’s a one-in-a-million chance, but we can create
platforms that make something more likely to be spread
• Viral videos are something executives or CEOs think are “fun” but there is really so
much that goes into video content creation than just simply throwing information and
footage together
• People need to research audience segmentations, consumers needs and wants, etc
before creating a video – there are really so many more components than video
creation. Just one step out of many.

2. What characteristics do you think help YouTube videos go “viral?”
• Platform success and an engaged user base
• Brand content and alignment to audience needs
• You can create a great video, but if it’s not properly aligned with your audience, it’s
not worth making it the first place.
• You need a great connection to make something have the possibility of going viral.

3. How often do you suggest companies and organizations to re-evaluate their digital

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strategy?
• Youtube is the most expensive platform
• If you don't have people already on the platform, there's not going to be a large
audience to truly make a difference.
• Just think, with ad buys, viewership needs, etc it really takes a lot of purchased space
to make a video a success.
• So, if you want to ROI, you need to invest in it.

4. What tactics do you use to share videos?
• Influencers
• Ad space and ad-buys
• ShareThrough
• SEO

5. How many hours does your team spend publicizing one promotional video?
• Different for each video
• Depends on budget and time
• Depends on how much notice given
• More than just promoting but rather what adbuys space will be most effective

6. What do you measure besides video viewership?
• Sentiment, comments, long-term metrics volume of views, engagement, views,
thumbs up and down
• It depends what the goal of the campaign is

Other notes:
• You only have 3-5 seconds to get the audience hooked. If you can’t to do it 3 seconds,
not worth creating and spending money to promote.
• Another important question to ask it HOW long are people viewing where you drop
them off at – for example, are people actually purchasing or following through with
the action you’ve assigned to them? If not, not really a success that can be directly
contributed to ROI
• However direct response doesn’t always have to buy in purchase power - being in the
moment - paid search
• More views, longer views - way more cost effective in YouTube
• SHOW them and they don't click - click-to-play rate

Interview 2: Will Dekrey, network expansion
• There are commonalities in ways people interact and how people within networks
share and create information. It’s finding how those work and unlocking the
capabilities of each network that can create huge differences

1. Can you explain a bit about the importance of networks for social good?
• Networks are the basis for how to expand ideas and generate support

73

• Really, with an organization or business, networks are vital
• But, when it comes to social good organizations, understanding networks becomes
very important
• Everyone has a unique network, and unique ties within the network. Understanding
how they intertwine and lead to other network is what can open doors to expand ideas
and generate support
• Membership organizations have the ability to grow and create people who really want
to spread the message and ideas

2. Can you explain a bit more about membership organizations?
• Communications professionals in philanthropy have used membership-based systems
to encourage people participate
• This is where network theory can really help
• Inside organizations, there is a high degree of trust, high degree of shared information
• Networks that are self-similar are not so good and problems solving and innovation
• Different compositions of networks lead to results that produce unique features and
ideas

3. How can that idea of network membership be used for social good?
• Hub and spoke model is standard and very popular for beginning network theory
• Dispersing individuals, but if you can bring together, but could lead to stronger ripple
effects
• Hub and spoke has the ability to rely on peer networks and support
• The way to expand is to make sure you’re talking and having an effect on people
outside of your network
Kaboom example:
• How do we ensure that every child has access? You need to spark behavior change

4. What network have you seen that has made the biggest ripple effect?
• Not one type of network, but best matching your network to creating change.
• Spread information – ideal behavior change – problem solve
• Pace of innovation
• Possible answer is strategy, goal setting – transparency, networks of constituents

5. What's your model of change?
• Empower a network – you want them to want to spread information
• Distribute power and distribute for a stable environment
• Collaboration between networks is what makes a movement
• Concept of working collaboratively is there, but not connections

Interview 3: Dan Neri, Head of Matter Media
1. Digital media is moving towards more image and video based content, what are your
thoughts when people or clients want a "viral video success?"

74

• Asks them – do you really know what viral success even means?
• Feel some people need to better understand what they are asking for or what their
reasoning is. For example, you should never put content out for the sake of just putting
content out – instead there should be a goal, a reason and a WHY factor that entices
people to do an action or feel a certain way.

2. What characteristics do you think help YouTube videos go “viral?”
• Some videos and ideas just have that spark. I can’t really say exactly what makes it,
but it’s an emotional connection.
• Whatever the case may be, the audience must feel and be compelled by the emotions
• The best way to create an emotional response is by using pictures and visuals to do so.

3. How often do you suggest companies and organizations to re-evaluate their digital
strategy?
• So specifically change based on a company or organization, however it is important to
stay current and new.
• It doesn’t need to be something crazy, but instead, if it can be something that is truly
compelling and touching the targeted audience, now that’s the best part.
• Sometimes in order to fulfill that need the strategy needs to be switched up a bit.
• You’ve got to ask yourself can other people do this? If anyone else can do it,
DISCOUNT it – you need that strategy and extra step that only your company or
organization can pull off.
• Are we being brave enough? Is this different enough? These are the types of questions
to ask.

4. What are the best end goals or objectives for videos?
• Ex: The third most visited website is PETA, but the most important part is that some
people spend 45 minutes on the site. Now that’s what’s interesting. Everyone’s
objectives are different and now days there are ways to measure everything. But why?
But how? To have people stay on a video longer? To share the video? To watch videos
after that?
• Wish I could say they have a formula, but they don't. It’s more important to know your
organization’s needs and goals and then branch from there.

5. Other Notes:
• There are so many variables for things going viral, something as simple as relying on
someone big to share it or it can just depend on the moment. But, what we can’t rely
on that.
• The marketing world was so different just a few years ago, and while people suggest
that this changes per platform, it’s the same idea. People want to be talked to like a
friend, not like a marketer. No matter what platform, it’s psychology and interactions.
How can we get people to feel that emotional connection to the information?
• What do the number of views mean to you? It’s hard to say what number of views
mean, but instead the important of a great end –result.

75

• Good storytelling, have showcasing conflicts and enemies are always classic ways to
show that emotional spirit.
• Hijacking events like the superbowl (ex: Oreos in 2013) has become a common way to
drive traffic.
• All brands need a conflict or a story to succeed.

76

APPENDIX 3: CONTENT ANALYSIS
Below is the content analysis of case study videos and the primary and secondary emotions
within each video.

Facebook(Followers
Regualrity(of(
Posting
Twitter(
Followers
Regularity(
of(Posting(
YouTube(
Subscribers
Number(of(
Videos Date Views Celeb Engagement Quality( Length
Primary(
Emotion
Secondary(
Emotion View(Type
CHLA 23,508 Daily 1,171
multiple(
times 3,487 351
Thank(You(To(
Selena(Gomez 1/12/12 3,446,616 Yes 12 6 2:42 Joy( Surpise High
Emily(Bear 6UJunU09 172,000 No 10 7 1:21 Surprise( Anticipation High
Breaking(News 2/26/12 88,257 No 0.01 5 1:17 Surprise( Joy High
Tracy(Zazslow 8/12/12 466 No 0.0001 3 1:37 None None Low
Monitoring(help 9/3/09 1,557 No 0 3 4:15 None None Low
Make)A)Wish 500,326 Weekly 10,200
multiple(
times 14,389 148
John(Cena(Video(
Game 6/8/09 753,000 Yes 0.0001 4 1:42 Surprise Joy High
Salvador(Meets(
Kobe 4/8/11 500,000 Yes 0.00001 7 2:12 Surprise Joy High
Cole(Meets(Chris(
Paul 4/8/11 352,000 Yes 0.00001 4 2:13 Surprise Joy High
NYSE(Bell(
Opening 3/11/11 255 No 0 3 3:03 Antiicpation Surprise Low
Macy's(Believe(
Campaign 5/29/11 170 No 0 7 :20 Antiicpation Surprise Low
Grades)of)Green 1,669 Daily 796 daily 12 24
Imagine( 5/16/11 753 No <1 5:01 High
Nolan(Gould 6/1/12 709 Yes <1 2:07 High
Couriosity(Quest 6/1/11 646 No <1 4:39 High
MBMS( 6/6/12 10 No <1 1:47 Low
Chadwick 5/1/13 10 No <1 5:12 Low
PETA 112,746
Multiple(
times(per(day 132,700
multiple(
times(daily 66,357 300
Boyfriend(Went(
Vegan 2/6/12 3,193,400 No 1 9 :31 Sadness Anticpation High
China(Fur(Trade(
Exposed(in(60(
Seconds N/A 3,042,433 No 0 9 :59 Digust Sandess High
Too(Much(Sex(For(
Jenna(Jamason 8/12/08 2,120,326 Yes 1 9 1:10 Surprise Anticipation High
Patiricia(De(leon( 2/1/08 4 Yes <1 0 :32 Fear Acceptance Low
Meg(Myers 7/7/08 3,574 Yes <1 9 :51 Digust Fear Low

77

APPENDIX 4: BUZZWORDS DEFINED
The idea of networks is collaboration between engineering, marketing, communications
and business ideas. Therefore, the words and phrases used may be unfamiliar to those outside
of the areas of study. With the hopes of making the following information as valuable as
possible, a few key words are defined below:
Engagement: The amount of interest your audience has for the content. Usually measured
in click-through ratings, time spent on content or the amount of times it was shared
Storytelling: The idea of creating a narrative within content and creating a brand
personality.
ROI: Return on investment is the idea that a company or organization gets the most out of
a time and financial investment as possible.
Social Capital: The amount of exposure someone is willing to risk on social media
platforms to voice an opinion.
Minimal Viable Product: The want to achieve the most exposure and change for the
smallest and most efficient time and energy.
Sharability: The want to create social media and multi-media images and videos that
people want to share.
Nodes: People of influence in the social network mapping or a connection point allowing
the transfer of ideas between people within one network.

78

APPENDIX 5: BEYOND THE HYPOTHETICAL
To best understand how to engage a disengaged network we utilized the suggestions,
outcomes and analysis to create a video experiment. While the content of the video was not
cause related, the “top 10” list above was given to the subject to see if someone who has never
posted a YouTube video could receive spreadable content. To start, he edited the video to 15
seconds to ensure the video fit the frame suggested. After creating his account, he then
uploaded the video to his other networks, as the above list suggests. After just one week he
was able to receive over 1,500 views and 17 shares. How did he accomplish this task with no
set network or subscribership?
The top 10 list as a summary of the qualitative and quantitative information and data
collected. The hope was that the information could be used from anyone beginning or
mastering digital strategy for content creation. Interesting roadblocks occurred during the
two-week trial video, which were recorded and summarized here.
First off, the interest in the video seemed to peak after less than 12 hours of being
published. In an effort to garner more engagement and a higher rate of interest, the subject
used network theory to call upon specific networked friends who may help him spread the
information to surrounding networks. By consistently asking a different friend with a different
network to report everyday, the subject was able to keep viewership up without noticing
another lag.
Additionally, after the video was on YouTube and asked people to share, he then
instilled a reason by telling people his video content was to win a bet. With a call to action a
means to help, friends then began to view and share the content at a fast rate. After only two
weeks of pushing content, the subject was able to reach the original objective of 1,000 views

79

and help better understand how untapped networks behave. Ebb and flows of networks made
the subject unsure of if the goal could be met. However after analyzing his own network, he
was able to rethink and garner more support.
The subject soon realized than while his own social media based network may not be
as easily convinced, his close friends and family would be. After calls and text, offline
communication, he was able to spark shares from those he considered his closest contacts.
After the combination of network analysis and content creation were mixed, the results were
quite interesting. After just a few days, the content as being viewed internationally, with
views in Australia, Germany and Canada being the highest international viewership rate.
Additionally, the keyword tagging became crucial, with keyword searches immediately listing
it as it’s first video.
While this stunt by no means states that the tips can create a viral video success, it
does demonstrate that the tips help create spreadable content by combining content creation
specifics and network analysis features.

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Asset Metadata

Creator Gee, Emily Joann (author)

Core Title Utilizing networks and digital distribution strategies to create spreadable video content for change

School Annenberg School for Communication

Degree Master of Arts

Degree Program Strategic Public Relations

Publication Date 09/30/2014

Defense Date 09/23/2014

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag digital,network,nonprofit,OAI-PMH Harvest,social good,strategy,Video,YouTube

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Thorson, Kjerstin (committee chair), Floto, Jennifer D. (committee member), Wang, Jay (committee member)

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