Group A: Megan Handerhan, Jordan Wise, Hannah Townsend and Kelsey Hensley Dr. Chris Yang May 10, 2012 COM 3928:101

Motivations for Passing Along Viral Videos Among Young Adults (18-35)

INTRODUCTION

The purpose of this study is to find out how young people aged 18-35 watch and pass

along online videos, their attitudes toward passing along online videos, and their reasons and

motivations of passing along viral videos. This study will show us how significant viral videos

are to the younger generation and the impact it can make. There are several motivations

regarding the passing along of viral videos which include: social influences, for personal

fulfillment , for entertainment and for political reasons. These variables were tested and will later

be discussed.

LITERATURE REVIEW

Watching and posting videos online became more popular a few years ago when websites

like YOUTUBE came about. Those sites open the doors to people posting their own information

or entertainment. People could have control and influence. Eighty percent of Internet users in the

United States have viewed or downloaded an online video (Beyond Access[HY1] ). People have

taken this idea further, to post videos uploaded by someone else. Some post to their social media

site, some email to a friend, and some just pass a video along through personal interactions.

Some of these videos are passed along so many times, they are said to be “viral.” What makes

these videos become so popular? What makes people spread viral videos?

According to the research and analysis of several articles, the motivation to forward and

pass along viral videos may be broken into four categories: 1) social 2) personal fulfillment 3)

entertainment and popular culture 4) political. Each of these categories can be broken down

further to examine specific reasons.

The first motivation that leads to viral video sharing is social status . To be included, to

gain attention and affection from others, and to control social standing are three main driving

forces for video sharing linked with social relationships (Haridakis and Hanson 316-32). It has

also been found that concepts of trust, normative influence and informational influence are

positively associated with using social sites that involve these kinds of videos (Chu and Kim 47-

69). It can be interpreted that these same concepts can influence the sharing and forwarding of

viral video ads. People want to feel included and informed and want to feel socially accepted.

In addition, studies have shown that people who watch reality television with friends are

more likely to post viral videos than those who watch alone. This idea is linked to the idea video

sharing is a behavior most in line with the values of reality television because it leads to

popularity or fame of participants (Stefanone 964-82). With this research, people seem to strive

for a celebrity status, which would be similar to those of reality television stars. Video-sharing

sites and the rise of viral videos opened up the idea that anyone can become famous (Kevin

Allocca: Why videos go viral).

Research also shows that people who are more outgoing in social setting post more than

those who are more introverted. People who are more active in social sites online, who are

“digital literate”, tend to share videos and enhance their digital literacy (Beyond Access). This

influences online social status, a new concept.

The second motivation is personal fulfillment. A study that coded 880 responses of

motivations for consuming videos found that consumers did so because it was entertaining,

relaxing, and interesting. Videos also offer a convenient escape from boredom (Chen 2008).

The third motivation is entertainment. The use of celebrities as entertaining factors

sparks interest and emotion, along with the likelihood of being shared. Research also shows that

novelty plays an important role (Southgate, Westoby, and Page 349-65). In addition, sharing

videos has become a form of entertainment and fun (Smith 559-61). It has become “normal” and

is transforming into another form of entertainment, almost another part of social media.

Celebrities and popular culture also influence viral video sharing by sharing videos

themselves. When famous people or blogs share videos, they earn the label of “tastemakers.”

Fans and followers become interested in these videos because someone in popular culture finds it

important. This increases the likelihood of forwarding and sharing the video (Kevin Allocca:

Why videos go viral).

The fourth motivation is political support. In the 2008 election, 25 percent of people

turned to the Internet for political news and 4 in 10 of the younger cohort have watched political

videos online (May 24-28). These videos began to go viral when campaign supports shared and

reposted them (Wallsten 163-177). Research also shows that people share political videos to

start discourse and democratic conversation ("Conference Papers -- International Communication

Association" 1-22).

Some political videos cross over to the entertainment motivation and involve levels of

amusement and comedy ("Conference Papers -- International Communication Association" 1-22).

This is an example of a primary motivation, political, and a secondary motivation, entertainment.

Many of these motivations can follow this same idea, influencing on another.

In conclusion, these four motives seem to be the most prevalent through our research.

Social status (capitol), personal fulfillment, entertainment and popular culture and political

information have been found to have the strongest links to viral videos and why students pass

them.

HYPOTHESES

From what we found through previous studies, personal interviews, and other research,

we were able to make several hypotheses about the motives for passing along viral videos. First,

we concluded that college students pass along videos to gain social capital or improve social

status, and this motive is positively correlated to the number of videos they pass. This leads to

another, similar, hypothesis that people pass along videos to conform and be like others. In

addition, we believe that students who watch many viral videos are more likely to pass those

videos along. To go along with this, we believe that a student’s use in social networking sites

influences them to pass along videos, and gives them a platform to do so. From our literature

review, we were also able to hypothesize that there are political and informational motivations

behind passing along viral videos. Lastly, we have also concluded personal fulfillment, whether

it is entertainment or informational, is another motive. In order to analyze and test our

hypotheses we use Pearson’s Correlation and multiple regression.

THEORIES

After finding out our testable hypotheses we came up with two theories to support them.

The first theory we are able to apply is the theory of planned behavior. This theory links attitudes

with perceived behavior to understand why a person performs certain actions (Ajzen). The theory

states that attitude toward behavior, subjective norms, and perceived behavioral control, together

shape an individual's behavioral intentions and behaviors (Ajzen). Below is a model of the theory

of planned behavior developed by Icek Ajzen. This theory applies to our research because in

order to find out why young people view and pass along viral videos (behavior), we must find

out their motivations (attitudes) for doing so.

The second theory we used is the Technology Acceptance Model (TAM). TAM assumes

that perceived usefulness and perceived ease of use determine an individual's intention to use a

system with intention to use serving as a mediator of actual system use (Furneaux 2006). In other

words, TAM explains why and how users come to accept and use technology. The model, shown

below, suggests that when a person is introduced with a new form of technology, such as social

media or online videos, a number of factors will influence the way they use that technology. This

model tests the theories behind a person’s motive(s) to share viral videos because the TAM tells

us that when a person is introduced to a new technology (viral videos) they will either accept or

reject the technology, and if they accept it, they will find new ways to use the technology.

METHOD

In order to get quantitative information to uncover information about viral video usage,

our group conducted ten personal interviews each. As a group, we conducted forty interviews

overall. We used convenience sampling for our personal interviews and the locations of the

interviews varied between Boone and Raleigh, North Carolina. Over 90% of the people

interviewed were college students ranging from 18-24 years old. We asked questions pertaining

to typical Internet usage and the frequency of viral video sharing. If the interviewees did not

share viral videos, we asked for their reasoning. This way, we gathered information about why

they shared videos and why they did not share videos. We then asked how they shared videos

with their friends, if it was through social networking sites or through email. We also asked how

they felt when they received a viral video from a friend or relative.

The next step in uncovering information about viral video usage, our class conducted a

web survey that reached 2,700 students at Appalachian State University. We worked together as

a class to develop a survey questionnaire with no more than forty questions based on our

professor’s draft to find out how young people aged 18-35 watch and pass along online videos,

their attitudes toward passing along online videos, and their reasons and motivations of passing

along viral videos. Once the survey questionnaire was ready, we conducted a pilot survey and

filled out twenty surveys as a test run. After the test run was complete, we hosted the survey on

surveymonkey.com and began to choose our samples.

We used random sampling by using the student phonebook for Appalachian State

University. Our class was then sectioned off into three groups with each group reaching 900

students each. We then used our personal emails to contact students through their school email

addresses. We did not send out the emails at once, instead we sent them out in intervals over a

span of ten days. We hoped this would increase our chances of getting the most responses. In our

emails, we used a form letter provided by our professor. There was an incentive of the possibility

of winning a $100 gift card for Amazon.com if the students decided to fill out the web survey.

We provided an incentive in the hopes of increasing the response rate. (citation of some sort as to

why we decided to use an incentive?) Once the first wave of web surveys were filled out, we

then figured out which students did not complete the survey. After we figured out the non-

respondents we sent out another email reminding them of the $100 gift card incentive and how

we did not have enough responses to conduct an accurate experiment. After two more days of

sending out emails in waves of 100, we gathered enough web survey responses to be reliable.

The measurement scale with response options ranging from “strongly disagree” to

“strongly agree” were adapted from Harvey, Steward, & Ewing (2011) and Huang, Lin, & Lin

(2009). The questions pertaining to perceived recipient’s interest and perceived risks were based

on 150 personal interviews of co-investigators and Palka, Pousttchi, & Wiedemann (2009).

Image outcome expectations and affection outcome expectations were questions adapted from

Huang, Lin, & Lin (2009). Survey questions that asked about normative pressures, perceived

control perceived enjoyment, and perceived expressiveness were adapted from Nysveen et al.

(2005). The final question relating to attitudes toward passing along online videos was adapted

from Yang and Zhou (2011).

We used the multiple regression and Pearson Correlation statistical methods to analyze

the survey data.

RESULTS

We conducted Pearson’s correlation to help us determine how accurate our hypotheses

were. We found that there are positive correlations, but some motives having a stronger

correlation than others.

Overall, all of the hypotheses have a positive correlation because the sig. is less than .05.

According to our data analysis, they are all significant at p < .05. All four of these are supported

because there is a positive correlation significant at p < .05 level. They have different levels of

relationships, however.

There is a moderate to strong, positive relationship between intent to pass along viral

videos and number of videos shared, with the Pearson’s Correlation being 0.602. There is also a

moderate, positive relationship between attitudes and intent, with a Pearson’s Correlation .582.

Pleasure and videos also share a moderate, positive relationship, with a Pearson’s correlation of

0.467. There is a weak, positive relationship between affection and videos shared, as seen in

a .326 Pearson’s Correlation.

The dependent variable was the number of videos young people pass along. The variables listed

above are the independent variables. According to multiple regression statistics, the independent

variables including social media use, video watched, and intent are significant predictors because

their beta weights are statistically significant at p < .05 level. In other words, the number of

videos passed along are influenced by social media use, videos watched, and intent.

DISCUSSION

Our final survey research results have good reliability and validity. We should be able to

draw some conclusions and make some recommendations for advertising practitioners or

communication professionals regarding using viral videos.

Our first hypothesis was that college students pass along videos to gain social capital or

improve social status, and this motive is positively correlated to the number of videos they pass.

Through our research, we found this to be correct. We also hypothesized that people pass along

videos to build social capital of affection. Through our study this has also been found to be true.

Our third hypothesis was also found to be correct. The idea that students who watch many viral

videos are more likely to pass those videos along was found true through our research. Our

hypothesis that student’s use in social networking sites influences them to pass along videos, and

gives them a platform to do so was found to be correct as well.

A few of our hypotheses were not studied through our interviews and surveys. First, the

hypothesis that there are political and informational motivations behind passing along viral

videos. Also, we believed that personal fulfillment, whether it is entertainment or informational,

is a motive for passing along videos.

CONCLUSION

Through our research we found that intent, attitudes, pleasure and affection are all motives for

passing along videos. Intent has the strongest relationship, meaning that within the next seven

days they plan to pass along viral videos to their friends. Attitudes has a moderate, positive

relationship to passing along videos. Pleasure and affection both have a weak relationship, but

are still positively correlated. This positive correlation throughout these motives prove they are

all significant.

LIMITATION AND FUTURE RESEARCH

One of our major limitations was that the interviews and surveys we conducted did not

examine either informative or political factors. Those were two of the major motives we found in

our literature review and based our hypotheses on. This left us without any information about

these categories and we were unable to make any conclusion. In the future, those are two motives

that should be added to personal interviews and to the questionnaires and surveys.

Our study was also hindered by the participants we had. We only interviewed students at

Appalachian State University. This only gives us a small glimpse into college students as a

whole. To make stronger generalizations, we should survey students from universities across the

United States. This would give us a better overall idea of college students motives for passing

viral videos.

Maybe look at highschool students as well. Choose a range of different universities. Get

more respondents. Look at more possible motives, rather than just social capital and attitudes.

Income as a demographic variable should also be eliminated since most college students do not

have a steady income and may still rely on their parents for money.

Another limitation in our research was our lack of knowledge regarding statistical

analysis and interpreting the data results. This hindered us from understanding the results

properly and being able to decode their meanings. In the future, in able to have a better

understanding of data analysis and how to decode the data, we will need to increase our

knowledge with regards to the statistical results . Our research would be easier to explain if these

limitations didn’t exist.

All in all, we conclude that we need to spend more time conducting surveys, focus groups,

interviews, convince samples, etc. in order to gain more results and maybe even more

perspectives. We would further our research to different colleges, not just Appalachian State

University. Most importantly, we would spend more time becoming more familiar with decoding

and understanding the results of our research. After we eliminate and/or overcome these

limitations, then we will be able to better our future research.

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