Thesis - A Little Birdie Told Me

Twitter and H1N1 1 

Running head: TWITTER AND H1N1

A Little Birdie Told Me:

H1N1 Information and Misinformation Exchange on Twitter

Tonya Oaks Smith

University of Arkansas at Little Rock


Acknowledgements

American writer Cynthia Ozick said “We often take for granted the very things that most

deserve our gratitude.” I would not have truly engaged in the process that is the Applied

Communication Studies Program in UALR’s Department of Speech Communication if I did not

take the time to thank the myriad individuals who helped me along the way. Here, I would like to

thank many people who were dedicated in their own ways to my success in graduate school.

My parents have always been the most supportive imaginable. I especially appreciate my

mother’s strong example in earning her master’s degree when she had a family to take care of;

she proved anything can be done with hard work and perseverance. Thank you both for believing

I could complete this step in my educational journey. My husband and daughter deserve to have

their names included as authors of this research paper as much as I do. They helped me check

formatting and sources and dealt with my anxiety and sleep deprivation. I am thankful for their

joining the collective and their sacrifices to get us where we are today.

Dr. Avinash Thombre has been a true inspiration in this process. His background is

similar to mine, and we were able to make a great team when it came to interpreting Ev Rogers’

Diffusion of Innovation and applying that work to my research. The other professors on my

committee – Dr. Rob Ulmer and Dr. Julien Mirivel – gave excellent advice to strengthen my

arguments. I am indebted to each of these men – as well as the other professors in the Speech

Communication Department – for their contributions to my education. Through you all, I have

learned what Krishnamurti meant when he said, “There is no end to education. It is not that you

read a book, pass an examination, and finish with education. The whole of life, from the moment

you are born to the moment you die, is a process of learning.” I hope to learn from each of these

professors’ examples and be a leader in the work for excellence in communication.


In the completion of this project, I depended on a number of friends to read sections,

respond to questions, and tell me if my reasoning made sense to someone who was not a

communication scholar. I so appreciate your indulgence of my work, and I commit here to

returning the favor when needed.

Finally, I’d be remiss if I did not thank the multitude of people who inspire me each day

with their work in the field of computer-mediated communication. With all of us working

together, we will establish a generation of ethical communicators who just happen to practice

their craft on their Internet. I’m incredibly proud to be a part of that group of individuals striving

for excellence in communication every day.


A Little Birdie Told Me:

H1N1 Information and Misinformation Exchange on Twitter

Today, people expect to share information, not be fed it. They expect to be
listened to when they have knowledge and raise questions. They want news that
connects with their lives and interests. They want control over their information.
And they want connection – they give their trust to those they engage with –
people who talk with them, listen and maintain a relationship.
– Michael Skoler, 2009, p. 39

Since 1997, computer programmers have worked to develop social networks that make it

possible for users to connect with others who share common interests. The first of those

networks, SixDegrees.com, allowed individuals to establish profiles, list friends, and connect

with others who have similar interests and contacts (boyd & Ellison, 2007). In effect, the advent

of social media allowed users to share information, just as Skoler noted. Individuals began to

control the data they received (Skoler, 2009). The phenomenon has grown since then to include

sites focused on music, job hunting, buying and selling used items, and blogging (boyd &

Ellison, 2007). One of the newest introductions into the world of social networks is Twitter, a

microblogging site that restricts user posts to 140 characters or less. According to Twitter’s chief

operations officer, in June, the service boasted 190 million users who post about 65 million

messages per day (Schonfeld, 2010). This number is growing almost exponentially each month;

in April, 180 million users were recorded (Schonfeld, 2010).

Developing connections among individuals with common interests is only one way that

social networks are used. The worth of the Internet has increased as individual users have

realized the value of connecting with other people, changing the perception of the Web from “a

one-way broadcasting or publishing medium” to a one that allows individuals to create valued

interpersonal networks (Gordon, 2009, p. 7). Internet-based communication channels can also


pass along information to consumers and diffuse data to a group of individuals who are in one’s

inner circle. Twitter helps users “make better choices and decisions and, … creates a platform for

[users] to influence what’s being talked about around the world” (Twitter, 2010). Individuals

around the world use Twitter to learn and then share their knowledge with other users. Therefore,

the medium stands as a one of the powerful new ways we use the Internet to diffuse information

within networks of individuals who are alike in their beliefs (Rogers, 2003).

Ev Rogers’ theory of Diffusion of Innovation focuses on diffusion as a “process by which

an innovation is communicated through certain channels over time among the members of a

social system” (Rogers, 2003, p. 11). Twitter is not only a new innovation itself, it is a prime

communication channel many individuals use to share information about their lives and interests.

In particular, users employ Twitter to share news events – either with a small impact like the

birth of a child or large impact like the spread of the H1N1 virus. Social media, including

Twitter, have dramatically changed how individuals share and receive information and news

(Ludtke, 2009).

With this research project, I analyzed the diffusion of information about H1N1 flu on

Twitter. I used the theoretical lens of diffusion of innovation to examine the information-sharing

behaviors of individuals on Twitter. To begin, I briefly explain the new communication

phenomenon known as Twitter and the H1N1 virus as well as its progression throughout the

world. Then, I examine the research that other scholars have completed on computer-mediated

communication, diffusion of innovation, and health communication. Next, I outline the research

methodology followed in order to examine how individuals used Twitter in the midst of a

worldwide health crisis. The paper details content themes within the online discussion of H1N1

and then I draw parallels between individuals’ use of Twitter and how this use of the medium


helped these people make a decision on whether or not to vaccinate themselves and their

families. Finally, I offer analysis of what the content analysis and survey data mean as well as

suggestions for the future use of Twitter to communicate pertinent information – particularly

health information – more effectively as a part of a well-rounded communication plan designed

to diffuse innovations and change behaviors.


A Twitter Primer

Twitter was developed in 2006 after years of work by co-founders Biz Stone and Evan

Williams (Malone, 2009). Twitter allows users “to post short text messages – called ‘tweets’ – of

no more than 140 characters on their personal feed” (Malone, 2009). The innovation is

commonly called microblogging, and an individual’s followers can read posts. Since its

inception, the tool has been used to communicate the mundane – information about what an

individual has eaten for dinner – to the incredibly important – information on the forced landing

of American Airlines flight 1549 in the Hudson River (Malone, 2009). Indeed, during the 2009

presidential elections in Iran and subsequent citizen revolt, Twitter was the only way residents

could get information to the outside world about the government’s actions (“Twitter links Iran,”

2009). Apparently, Iranian officials did not assign much importance to this new innovation, but

its power is growing exponentially as the number of adopters grows.

Twitter can be used to talk to one individual or a small group, in the same fashion as

interpersonal communication, or to millions, in the same way as mass media are used. In fact, the

medium allows individuals to embrace the old-style idea of journalism and interpersonal

communication, one that delivers news to help readers “connect with neighbors, be active

citizens, and lead richer lives” (Skoler, 2009, p. 38). The innovation has been wholeheartedly

embraced as a result of this change in thinking about communication – the movement from one-

way to reflexive (Gordon, 2009). In April 2009, over 7 million unique visitors used the site,

proving the application’s reach and influence in the social networking community (McGiboney,

2009). Currently, Twitter users share 65 million messages per day (Schonfeld, 2010). Thus,

Twitter shows promise for communicating useful information to multitudes of people in real

time, as shown in Figure 1 below, completed with information from Compete.com, a web


analytics company that monitors the use of websites with surveys of over 2 million Internet users

in the United States. These users gave the company their permission to analyze their web usage

as well as conduct surveys into their habits on the Internet (Compete.com, 2010). This

communication tool roughly follows the traditional S-shaped curve that Rogers (2003) states

innovations will adhere to during the innovation-adoption process.

Despite the fact that Twitter can – and is – used to share positive information, the tool can

also be used to spread misinformation, as can be seen in the beginning of the H1N1 outbreak in

spring 2009. Journalists commented in April 2009 on the microblogging site’s becoming “a

hotbed of unnecessary hype and misinformation about the outbreak” (Sutter, 2009). Tweeps, as

those who post on the site have become known, spread information about the false connection

between consuming pork and the flu, the possibility of germ warfare, and other assertions about

the disease and its spread (Day, 2009; Morozov, 2009). The ease with which misinformation can

be spread, as well as the possibility of information overload, or “the state of an individual or a

system in which excessive communication inputs cannot be processed and utilized, leading to

breakdowns,” are two of the prime problems seen with using Twitter as a communication vehicle

for important information (Rogers, 2003, p. 368-369).


29

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Users in Millions

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22

21
Jul-09

Aug-09

Sep-09

Oct-09

Nov-09

Dec-09

Jan-10

Feb-10

Mar-10

Apr-10

May-10
Date

Figure 1. Graphical representation of the Twitter adoption curve – an S-shaped curve.
Data course is Compete.com.


H1N1: The Health Crisis

When a crisis occurs, individuals instinctively seek information that will help them

alleviate their uncertainty. They want to acquire data that will help them process their situation

and respond effectively to the danger it presents (Ulmer, Sellnow & Seeger, 2007). The H1N1

outbreak, which began in April 2009, is no different than other health crises such as the Severe

Acute Respiratory Syndrome (SARS) outbreak of the early 1990s or the Human

Immunodeficiency Virus (HIV) and Acquired Immune Deficiency Syndrome (AIDS) outbreak in

the 1980s. Many individuals sought to create self-efficacy, the perception of an individual’s

“capacity to organize and execute the actions required to manage prospective situations”

(Singhal & Rogers, 2003, p. 313-314). However, with the latest health crisis that the H1N1 virus

outbreak presented, a number of new communication media were available that simply did not

exist in the late 20th century. Twitter was one of the many ways that individuals employed to

collect information on the virus and how to avoid contracting it. Both the World Health

Organization and the Centers for Disease Control and Prevention utilized the new medium to

communicate timely information on the virus to their followers.

When the H1N1 virus was first diagnosed as a unique illness in April 2009, the Internet

came alive with stories from around the world of those who were sick with the illness. The first

documented death occurred in Oaxaca, Mexico, and health officials there declared the death as

an isolated incident, even though individuals who had been in contact with the deceased woman

were suffering mild symptoms of pneumonia (World Health Organization, 2009a). Soon after,

there were other deaths from the same illness, which was then feared to be avian flu, and the

Mexican government reported the illnesses to the World Health Organization (WHO). Some

American travelers returned home from Mexico with symptoms of the mystery illness, and they


were advised to stay home until a cause could be found (Chen, 2009). Canadian health officials

determined – after studying samples sent from Mexico – that the virus was not avian. Instead, it

was found to be the H1N1 “swine flu” virus (WHO, 2009a). Later in April, the first H1N1 cases

were reported in the United States, and the WHO declared a health emergency on April 26. At

that time, there were a total of 40 cases of the H1N1 virus in the United States (Cable News

Network, 2009).

The number of H1N1 cases rose almost exponentially in the following months. In June

2009, 74 countries had verified H1N1 infections, and WHO director general Dr. Margaret Cho

declared the virus outbreak a pandemic (WHO, 2010). The virus was different in that it caused

high rates of infection in the summer, when most viruses are largely dormant. The virus was also

unique from other seasonal flu outbreaks, according to the WHO, because

pandemic H1N1 was a new virus when it emerged and most people had no or little

immunity to it. In addition, one of the lessons from history is that influenza pandemics

can kill millions. Finally, there was no pandemic influenza vaccine at the outset (WHO,

2010).

In addition, individuals who were not normally susceptible to flu hospitalization and death –

namely young adults – experienced the highest percentage of deaths by age group (See Figure 2).

After the initial surprise of discovering that a new H1N1 virus was running rampant in

many countries, both the CDC and the WHO worked to respond to the crisis by sharing

information with those who might be negatively impacted. They utilized unique approaches to

communicate information, and through their work, uncertainty was alleviated (Ulmer et al.,

2007). Both organizations posted information regularly to their Twitter feeds –

twitter.com/whonews and twitter.com/CDCemergency – and held timely press briefings. Their


work to ease uncertainty positively impacted how individuals dealt with the crisis (Littlejohn &

Foss, 2008).

140

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100
Deaths

80

60

40

20

0
0-4 years
5-24 years
25-49 50-64 >65 years
Unknown
years
years
Age of Deceased

Figure 2. Bar chart of H1N1 deaths in the United States by age group. Source is the
Centers for Disease Control and Prevention.


Reviewing the Literature

In recent years, much research has been conducted on the formation of opinions through

the use of computer-mediated communication (CMC) and social networks (Black, 2007; boyd &

Ellison, 2007; Lyons & Henderson, 2005). Twitter, however, is such a new phenomenon that

scholarship has not caught up with the technology. The body of work instead focuses on the

construction of online personas and the use of social media to spread marketing information

(Neff, 2009). Since Twitter and other social networks are computer-mediated communication,

we will apply the same theories and techniques that other researchers have used in its analysis.

In addition to the formation of networks with CMC, communication research touches on

computer-mediated spread of misinformation, without connecting the construction of collective

truth and conversion to action through false information (Black, 2007; Eastin, 2001). Health

communication literature also focuses on the use of mass media to diffuse innovations and

encourage healthy behaviors. However, this section of the literature does not include

communication mediated by computers. In short, the literature fails to connect the dots between

traditional mass media and new media and their shared use as cooperative channels in the spread

of health information.

Sense Making

Authors have examined sense making with computer-mediated communication,

specifically Twitter, as well as the overload of data available in this channel (Farhi, 2009). In

addition, researchers have examined the information overload in the light of news consumers’

attempts to become active participants in the process of constructing news (King, 2008). The

process of gathering and productively using information in the digital age has changed

dramatically, and users must work to determine which information is true and which is false


(King, 2008). Researchers, however, offer no way to determine the veracity of data passed along

through digital channels or discuss the process by which users determine which information

allows them to develop self-efficacy (Botta, 2006). There is, however, a focus on reader

acceptance and contribution of information and misinformation to the new-media stream (King,

2008).

Researchers also attempt to provide a basis for how journalists and other news-gatherers

– including other Twitter users – regard the new medium. Companies respond daily to

misinformation spread through Twitter – either intentionally or unintentionally (Neff, 2009).

Their responses – and the analysis of these defensive communication acts – helps provide best

practices for response to misinformation could be used by for-profit organizations or government

agencies who are responsible for disseminating information about health crises in the digital age

(Eastin, 2001; Neff, 2009). Research has, however, contributed to the understanding of how truth

is constructed through public discourse, and this theory can be applied to analysis of new media

such as Twitter (Black, 2007).

Black, specifically, focuses on the formation of public knowledge and truth. His

argument centers on “how information, both factual and nonfactual, can evolve into truths within

the realm of public knowledge” (Black, 2007, p. 2). The researcher notes several instances of

how misinformation has been spread through word of mouth and mass media, entered into the

public consciousness as truth, and been acted upon. Black (2007) makes use of diffusion of

innovation theory in his argument, specifically the use of interpersonal communication to spread

ideas that then make their way into the public consciousness (Rogers, 2003).


Computer-mediated Communication

The literature also explores the differences between computer-based opinion leaders and

opinion leaders from more traditional environments (Lyons & Henderson, 2005). While the

characteristics for both groups are similar, computer-mediated opinion leaders are more

exploratory in their behaviors (Lyons & Henderson, 2005). Though the research provides basic

information on opinion leadership in a computer-mediated world, it does not examine the

blurring between interpersonal communication and mass media that computers allow those who

choose to use them to communicate. In addition, we have seen a contrast between the negative

and positive aspects of information sharing via CMC (boyd & Ellison, 2007; Eastin, 2001).

Media Intervention in Health Behaviors

Finally, much research has focused on media intervention in health behaviors,

specifically when individuals do not have enough interpersonal communication support to form

opinions (Singhal & Rogers, 2003; Botta, 2006). By applying the media dependence theory in

conjunction with research on the diffusion of innovation, Botta (2006) discusses the importance

of mass media when individuals have unmet information needs. The added information –

delivered by mass media – provides these individuals with messages of self-efficacy (Botta,

2006). In this article, the author focuses on behaviors associated with HIV and AIDS prevention,

but the theory could be applied to any health crisis. Information’s empowering force – especially

when delivered in a trusted forum – allows individuals to make intelligent decisions regarding

their health during crisis.

Each of these studies shows that information and misinformation are easily spread

through both mass media and interpersonal communication channels, including new media

channels. However, Twitter is such a new innovation – it has not yet become completely diffused


itself – that scholarship has not focused on it in a concrete way. Future researchers need to

extend focus beyond traditional mass media and examine new media in the same fashion. This

research project in part attempts to examine Twitter in the same light as researchers have studied

other communication channels.


Theoretical Framework

As an overarching theoretical tool, this research project uses Everett Rogers’ extensive

conceptualization of how an innovation spreads in a social system among its members. As

defined earlier, diffusion is the way that a new idea is shared through communication channels.

This spread takes place over time and throughout a social system (Rogers, 2003). However,

diffusion is more than simply wanting to ensure that a new idea will be shared. Instead, the best

examples of diffusion of innovation show that an idea has been adopted (Dearing & Meyer,

2006). Future scholars noted that education and mass media directly contributed to this idea of

successful innovation through adoption (Melkote, 2006). Whether that idea is planting a newly

developed kind of seed corn or using a condom to prevent the spread of AIDS, those who diffuse

the innovations want to ensure that the idea is accepted and adopted quickly (Singhal & Rogers,

2003).

There are several concepts within the theoretical framework that help us understand the

use of Twitter to diffuse information and how its use can help influence future health behaviors.

In this section of the research, I will focus first on the innovation-decision process and how

individuals follow this path to adopt or reject innovations. Then, I discuss communication

networks and why they are formed and used to diffuse information about innovations. I will also

utilize the concept of opinion leaders, showing how they are differentiated from change agencies

and agents. Next, I examine the differences between mass media and interpersonal channels,

discussing how each of these communication tools is used in different ways to diffuse

innovations. Finally, I will focus on disinformation and misinformation and how their use can

cloud the perceptions of message receivers, changing their minds on adopting innovations.


Innovation-decision Process

The process of determining whether or not an innovation should be accepted is known

throughout Rogers’ work as the innovation-decision process (2003). This five-step program (See

Figure 3) allows individuals to first work through a knowledge phase, where he or she learns of

an idea or innovation and how it works (Baumann, 2008). During this phase, “potential adopters

develop perceptions of the innovation characteristics, which are influenced by peers, change

agents, mass media portrayals, social norms, the kinds of innovation information needed, initial

experiences, and, in some cases, the adoption by others” (Rice, 2009). The individual then moves

through the persuasion phase, where he or she forms an attitude toward the innovation (Rogers,

2003). Then, the prospective adopter actually makes a decision and implements it in the third and

fourth stages of the process (Baumann, 2008). Finally, the decision and implementation must be

reinforced in the confirmation stage (Rogers, 2003).


Figure 4. Representation of the five stages in the innovation-decision process. Adapted
from Ev Rogersʼ Diffusion of Innovations.

Communication Networks

According to Rogers, communication is the “process in which participants create and

share information with one another in order to reach a mutual understanding” (Rogers, 2003, p.

5). The mutual understanding happens as communication brings together those who are in

similar circles – because of socioeconomic status, learning, or other factors. These

communication circles allow individuals to come to a conclusion about an innovation – namely

whether to adopt and use it or not. Information by itself cannot help an individual come to the

conclusion to adopt an innovation. Instead, personality – the very charisma that helps construct

an individual’s position as an opinion leader – is also necessary (Dearing & Meyer, 2006).

Integral to the idea of effective diffusion of innovation through communication and shared


agreements is the concept of a communication network, or a group of individuals who are

connected by sharing information on topics in their common interest (Rogers, 2003).

The effectiveness of communication networks can frequently be determined by the level

of homophily, or the “degree to which a pair of individuals who communicate are similar,” of the

individuals within those networks (Rogers, 2003, p. 305). While it usually adds to the level of

diffusion, homophily can sometimes serve as a barrier to innovation because individuals who are

similar in beliefs and behaviors do not interact with those who would most benefit from the

introduction of innovation (Leonard, 2006). For instance, those of higher status – the ones most

likely to encounter new innovations – rarely interact with those of lower status. Groups of

individuals who are too similar are also not as creative as groups of people who are slightly

different. These individuals simply don’t have to be creative. Their ideas are the same as

everyone else’s, and there is no reason to venture beyond their comfort zone to find remedies for

problems. Therefore, individuals who are too similar to their peers will lose the ability to serve as

opinion leaders and persuaders (Leonard, 2006). Parallel thinking dilutes potential opinion

leaders’ power and can bring the diffusion process to a standstill.

Contrary to homophily, heterophily is the dissimilarity between communication partners

(Rogers, 2003). Differences in opinions can cause cognitive dissonance, but these differences

can inadvertently work to strengthen communication between diverse cliques (Rogers, 2003). In

fact, in today’s rapidly changing world, creative friction is often necessary to inspire inventors to

create new products and processes (Leonard, 2006). However, despite the advantages that

infrequent communication and differences across social and economic boundaries can have to

help diffuse innovation, Rogers believed that homophily among interpersonal communication

networks is one of the greatest engines for change. Opinion leaders pilot these networks, and


their effectiveness is gauged on the “degree to which [they] are able to influence other

individuals’ attitudes or overt behavior informally in a desired way with relative frequency”

(Rogers, 2003, p. 27). Because these influential individuals are the ones who largely drive the

diffusion process, in the next section, I elaborate on the definition of opinion leaders.

Opinion Leaders

Change agents are the first individuals charged by a change agency – or an organization

working toward the adoption of an innovation – but they are frequently unable to directly impact

individual behaviors. Opinion leaders serve as the sergeants in the fight to diffuse innovations in

a system. They are closer to the average foot soldiers – and command these individuals’ respect

– than those who are at the top of the chain of command, or the change agents and agencies. In

much the same way a general’s ability to win a war is dependent on his sergeant’s ability to carry

out orders and influence others to carry them out, the success of a change agent is directly and

“positively related to the extent that he or she works through opinion leaders” to achieve the

agency’s goals (Rogers, 2003, p. 388). Because opinion leaders are closer to the actual

prospective adopters, they are able to impact behaviors more quickly and directly than the actual

agents of change. As stated above, Rogers believes that opinion leaders can share the innovation

through homophilious or heterophilious communication through these channels. Homophily,

however, is the strongest method of sharing information and converting behaviors. A successful

opinion leader must walk a fine line between being similar to those he works for and those he is

working to persuade. If diffusion is to be successful, opinion leaders must bridge the gap

between those who have diverse bodies of knowledge (Leonard, 2006).

Contrary to many change agents’ beliefs, those who adopt new innovations the quickest

do not often serve as true opinion leaders in a community. Opinion leaders are not innovators,


nor are they the first individuals to adopt an innovation or make a change (Rogers, 2003). These

people – early adopters – are frequently seen as deviants within a social system and do not garner

the respect that true opinion leadership commands (Rogers, 2003). Instead, opinion leaders are

individuals who have followers. They are respected in their community, and they are “sought by

others for their opinions and advice” (Lyons & Henderson, 2005; Singhal & Rogers, 2003).

When change agents are able to train influential individuals and send them out to spread the

message, then more persuasion is accomplished and innovations are adopted successfully.

Opinion leaders can share information in many ways, among them mass media and

interpersonal channels, which are discussed below. But one of the most effective ways for these

persuaders to share their knowledge is through a demonstration (Rogers, 2003). In fact, when

AIDS ran rampant through the gay community in the 1980s, the most effective ways of

spreading information about the effectiveness of condom use was through demonstrations and

interventions held in gay bars (Singhal & Rogers, 2003). Demonstrations help to increase the

observability of advantages involved in an innovation – one of the requirements for adoption

according to Rogers’ theory. Demonstrations are often effective, Rogers said, because they add

the “perceived competence credibility of the change agent with the perceived safety credibility of

the demonstrator” (Rogers, 2003, p. 390). Demonstrations are even more effective in creating

behavioral change or achieving adoption if the demonstrator is an opinion leader, or one who is

trusted to share authentic information about the innovation and the results of the demonstration

with those who fall later in the adoption cycle (Rogers, 2003). When the opinion leader is

outfitted with pertinent information and supplies from the change agent, then he or she is also

better able to share ideas and persuade individuals to adopt innovations (Adhikarya, 2006).

Demonstrations and pertinent information can be counted as two of the ways opinion leaders


engage in interpersonal communication with their target audiences. In the next section, we

discuss mass media and interpersonal channels, as well as the differences between the two and

how new methods of communication are serving to blur the lines between mass and interpersonal

communication channels.

Mass Media and Interpersonal Channels

In addition to utilizing demonstrations, opinion leaders can spread information through

mass media or interpersonal communication. Mass media channels, usually the most efficient

way to talk about innovations, are perceived to be the “magic multipliers of development

benefits, and as harbingers of modernizing influences” (Melkote, 2006, p.151). Interpersonal

channels, however, “involve a face-to-face exchange between two or more individuals” (Rogers,

2003, p. 18). The informal influence that opinion leaders exert often results from “product-

related conversation, referred to as ‘word-of-mouth’ communication” (Lyons & Henderson,

2005). In his theory, Rogers emphasizes the importance of both mass media and interpersonal

communication channels in sharing information during the course of a diffusion project. Opinion

leaders also have the opportunity to share pertinent information through interactive

communication via the Internet, and this method of communication has become “more important

for the diffusion of certain innovations in recent decades” (Rogers, 2003, p. 18). Scholars often

refer to this method of communication as “word of mouse,” and much study remains to be

conducted if researchers and change agents are to understand the power of computer-mediated

communication as either a mass medium or interpersonal channel (Lyons & Henderson, 2005).

Each channel has its own strengths and weaknesses, and change agents must determine

which one will be more effective in ensuring that an innovation will diffuse. In discussing the

innovation-decision process, Rogers asserts that “mass media channels are relatively more


important at the knowledge stage, and interpersonal channels are relatively more important at the

persuasion stage” (2003, p. 205). Researchers have found recently, however, that mass media can

substitute for interpersonal channels in certain circumstances, such as when an individual does

not have access to expert interpersonal communication (Botta, 2006). These two channels, while

very different, are connected by their focus on sharing message content that is “concerned with a

new idea” (Rogers, 2003, p. 18). Differences, especially in the age of more computer-mediated

communication and shrinking boundaries between communities, may be disappearing. The

Internet provides opinion leaders with both “an unprecedented repository of information” on a

number of subjects and the ability to share that information with an untold number of individuals

(Lyons & Henderson, 2005, p. 321). The innovation that we know as the World Wide Web has

opened up a new idea of opinion leadership and blurred the lines between social classes and

familiar groups.

How the spread of information is accomplished and how that information diffusion leads

to adoption of innovation figures heavily in this research. The discussion of opinion leaders and

the examination of new communication technology bring us to the following research questions:

RQ1: How is Twitter used as a communication channel for H1N1 information

diffusion?

RQ1a: How are opinion leaders determined on Twitter? What constitutes an

interpersonal network on Twitter?

Interpersonal communication and mass media channels are focused on sharing

information, or data that can change the level of uncertainty in a given diffusion situation

(Rogers, 2003). However, in order to effectively share an innovation, the information that is

shared must be accurate. The Internet has no “government or ethical regulations controlling the


majority of its available content” (Eastin, 2001). Because information is not verified, audience

members are forced to distinguish for themselves between accurate information and

misinformation (Eastin, 2001).

Misinformation and Disinformation

Governments have used misinformation and disinformation for centuries to control the

hearts and minds of their citizens and others commonly thought outside the normal sphere of

influence (Hachten & Scotton, 2007). Most often used during war efforts, misinformation is

employed to help control messaging, and the media are not immune to the ready flow of

incorrect information. While the aim of spreading incorrect information may be seen to be

negative, it has been used to positive ends. Of course, the perception of those ends depends on

which side of the conflict the audience supports. During Operation Iraqi Freedom, for example,

information has been tightly controlled, and some official news “was actually disinformation

intended to mislead the enemy, not to inform the public” (Hatchen & Scotton, 2007).

Broadcasters, however, acknowledge the need to give accurate information to viewers and

listeners (Clark & Christie, 2005). In fact, later in the Iraqi War, reporters and broadcasters

whose information was passed along in the Middle East recognized the importance of sharing

truthful information and established outlets to do just that (Clark & Christie, 2005).

The use of computers to share stories has muddied the water for those who seek

information from opinion leaders and other authoritative sources. While misinformation and

disinformation have always been available through both mass media and interpersonal networks,

the quickness with which individuals can communicate via computers has increased the amount

of incorrect information that can be shared with anyone and everyone all over the world (Seidel

& Rogers, 2002). Information innovations “have revolutionized the speed of information and


provided global reach coupled with easy affordability and accessibility for large portions of the

world population” (Mohammed & Thombre, 2003). There are several reasons that

misinformation and disinformation are so easy to share online. First, the Internet is a cost-

effective way to share data, and individuals who would serve as self-appointed opinion leaders

are no longer required to be members of news-gathering organizations or to show credentials for

their presumed expertise (Carmichael, 2003). Second, individuals and organizations working as

change agents or opinion leaders are able to publish “Websites with apparently greater authority

and with a potentially far larger audience than would otherwise be the case” (Carmichael, 2003).

While many embrace the effortlessness with which individuals can share information via the

Internet, this ease of exchange can negatively impact diffusion of innovation as well if

misinformation is shared.

Social media networks are prized for their focus on authenticity. But just as interpersonal

exchanges can share fallacies, the Internet can be a tinderbox for misinformation that causes a

wildfire in today’s rapid communication environment. If individuals have the capacity to

determine which individuals they will follow through Twitter, then researchers should determine

the answer to another research question:

RQ2: How do people on Twitter distinguish its credibility or lack thereof, and how

does this credibility influence their behavior?

Researchers have long engaged in studying news events for their salience (Seidel &

Rogers, 2002). The H1N1 outbreak surprised scientists and health officials with its speed and

ferocity, and its propensity to attack individuals who were not normally at risk for death from a

flu virus (WHO, 2010). In the beginning of the outbreak, the virus was a totally new

phenomenon, and there was a great deal of uncertainty for both officials and regular citizens


about how the virus was spread and how best to prevent that spread. Therefore, this news event

was highly salient for most individuals around the world.

In the same way, Twitter – and research on its adoption and use – has its own salience.

New media have recently become the topic of much more research (Tomasello, Youngwon, &

Baer, 2009; Kim & Weaver, 2002). Millions of individuals use the microblogging service each

day to send short messages to millions of other individuals. It is one of the newest methods of

communication, and people are still learning about its use in everyday life. In addition, Twitter

and other social media applications offer the opportunity for interactivity, which allows for

stronger relationship development and is considered a “central influence upon the outcomes

communicators take away from the interactions” (Ramirez, 2009, p. 301). The first stages of

Twitter adoption and the H1N1 virus outbreak share roughly the same timeframe. Each of these

innovations is worthy of study on its own. However, when two such important advances collide

in the way that Twitter and H1N1 did in mid-2009, researchers should take notice. In the

following section, I explain the methodology for exploring the significance of the diffusion of

information on H1N1 via Twitter.


Methodology

Both prior research and the theoretical framework of diffusion of innovation led to the

aforementioned research questions. In order to answer these questions, I defined a research

methodology that examines both the content that Twitter users choose to share and their self-

reported habits in communicating that information. To conduct research on the prevalence of

correct information and misinformation on the H1N1 outbreak that was shared via the web-based

communication tool known as Twitter, I employed a three-step data collection process. First, I

gathered data from Twitter and performed a content analysis. Next, I conducted a survey of

random Twitter users on their habits while utilizing the microblogging platform. Finally, I

performed interviews with a sub-sample of those who answered the initial survey in order to

further discern their Twitter use and behaviors. In the following section, I will describe each of

these steps in more detail, explaining the reasoning behind each of the research segments.

Step 1 – Content Analysis of Tweets

To begin, I collected individual posts from Twitter. This dataset – all Tweets ever posted

to the site – was randomly searched for postings that mentioned at least one of three terms:

Swine flu, swineflu, and H1N1. The resulting dataset numbered approximately 300,000. In order

to further reduce the number of posts to be examined, I isolated the Tweets sent on three key

dates – April 25, Sept. 4, and Oct. 24, 2009.

These dates were chosen for their relative importance in the progression of the virus

throughout the world. On the first date, April 25, 2009, the World Health Organization met to

discuss the epidemic and ways to deal with virus treatment and prevent the spread of the disease

(MSNBC.com, 2009). On Sept. 4, 2009, the second date in question, the number of deaths

around the globe ramped up, and the virus killed 625 people in the week prior (MSNBC.com,


2009). On the third date, Oct. 24, 2009, President Obama declared a national emergency to deal

with the flu outbreak, freeing up significant resources to deal with the issue (MSNBC.com,

2009). On each of these dates, Twitter traffic concerning the outbreak swelled in comparison to

Tweets about other topics. This increase in traffic led me to believe that the events occurring on

these three dates were important among Twitter users. By narrowing the dataset to these three

dates, I reduced the number of Tweet posts to be examined to 46,000. I determined this number

was representative of the original 300,000 as well as more manageable than the original dataset,

so I began the process of content analysis.

To start the content analysis, or the “procedure that helps researchers identify themes and

relevant issues often contained in media messages,” I read one-third of the dataset attempting to

avoid bringing preconceived notions about the Twitter posts’ themes (Rubin, Rubin & Piele,

2005, p. 223). By viewing the tweets, or “data as representations not of physical events but of

text, images, and expressions that are created to be seen, read, interpreted, and acted on for their

meanings,” I drew parallels between pieces of information from disparate sources (Krippendorf,

2004). From this content emerged common communication themes relating to the reasons

individuals share information via computer-mediated communication. After reading these 15,000

tweets, I was able to determine that Twitter users focused much of their online conversation on

four major topics.

Interest in content analysis is tied not only to the topics inherent in the individual posts

but also to the effect that the content has on those who send it and receive it (Rubin et al., 2005).

After determining the topics, therefore, I had to categorize those ideas into communication-

seeking or -giving posts. This classification is akin to Burgoon’s principle of interactivity, which

holds that “human communication processes and outcomes vary systematically with the degree


of interactivity that is afforded or experienced” (Ramirez, 2009, p. 302). Posts that noted

interactivity – or a desire for interactivity – were further categorized into one of three major

communication themes – health information, uncertainty reduction, or misinformation and

disinformation.

Step 2 - Survey

Following this content analysis, an online survey was designed to ask Twitter users on

how much H1N1 information they have obtained and the actions they have taken as a result of

that information was conducted. The survey was self-administered, and no prompting for

particular answers was given (Rubin et al., 2005). In order to encourage individual Twitter users

to participate in the survey, which was based on the online survey tool Survey Monkey, I posted

a Tweet requesting participation in a short survey about Twitter attitudes. I also asked for

followers to retweet the original post – “Help with research on Twitter and communication.

Survey here:” – and several assisted me with communicating information about the survey to as

many individuals as possible. After posting the request for participation once a week for a

month, I received 59 responses to participate in the survey. Only 42 of these 59 completed the

whole survey.

The survey form (Appendix A) was chosen to allow collection of individuals’ “attitudes,

opinions, and reported behaviors or behavioral intentions” (Rubin et al., 2005) about how they

use Twitter as a communication tool. Among the topics of interest in the survey were closed-

ended questions on the number of followers an individual user has – or how potentially large his

or her reach is – and open-ended and closed-ended questions on retweeting – passing along of

pertinent information between related users. In addition, I asked open-ended questions to

determine how long individuals had engaged in Twitter as a social medium, and how their – and


responses to prior tweets. In addition, I asked if individuals had received a vaccination for H1N1

and whether or not information they received via Twitter helped them reach a concrete decision

on vaccination for themselves and their families. This analysis helped determine how individuals

who use Twitter are able to serve as opinion leaders, and whether Twitter is being used as a

channel for interpersonal communication between related community members or if it is being

used more as a mass media channel with information being pushed out by subject matter experts.

Lastly, the survey helped ascertain whether or not Twitter was being used effectively as a tool to

create successful diffusion of information about H1N1 and the innovation of preventative

vaccinations for the pandemic flu virus.

Step 3 - Interviews

To complete the analysis of individuals’ personal and unique use of Twitter as a health

communication and uncertainty-reduction medium, I lastly conducted 10 short telephone

interviews comprised of two questions only. These interviews allowed qualitative answers to the

“why and how come questions” that concerned me when I examined the survey results. In order

to obtain a group of respondents for this section of the research, I again used Twitter to request

participation. I sent out an appeal for those who already responded to my survey to contact me

via direct message to further explain their involvement with Twitter. I contacted the first 10

individuals who responded and asked them two questions over the telephone:

• Did you or your family obtain the H1N1 flu vaccination?

• How did reading information on Twitter contribute to your decision to get this

vaccination?

In these interviews, I was able to obtain more qualitative data about where these

respondents’ information about H1N1 and vaccinations to prevent the spread of the disease came


from. By asking if individuals had obtained the vaccinations for themselves and their families

and where their information came from, I could further discern which information source served

as the tipping point for vaccinations and whether that information was supplemented with face-

to-face interactions (interpersonal communication) or news reports (mass media).


Results – Twitter Themes

Rogers’ innovation-decision process provides a framework for the analysis of Twitter

posts concerning H1N1 on the three key dates in the spread of the virus mentioned earlier. The

process allows an individual to go from being aware or learning about something that is new to

making a decision to use or not use it. Then, the individual must have his or her decision

confirmed. Rogers’ definition of this frame of understanding consists of five stages – knowledge,

persuasion, decision, implementation, and confirmation (Rogers, 2003). These five stages are

outlined in Figure 5 below.

Figure 5. Representation of the five stages in the innovation-decision process. Adapted
from Ev Rogersʼ Diffusion of Innovations.


During the knowledge stage of the process, individuals must receive and comprehend

enough information to be able to begin to make a rational decision on the adoption of an

innovation (Rogers, 2003). Mass media – like Twitter – work to create awareness-knowledge,

while interpersonal communication can be used to tie individuals together and begin to help

individuals enter the persuasion stage of the cycle. Though different, interpersonal

communication also involves the transfer of knowledge. In fact, all innovation diffusion

processes begin with the acquisition of knowledge from a vast array of sources (Leonard, 2006).

During the information stage, individuals are able to discuss the innovation within their

social systems and start to gain support for their change in behavior from inside the system. Mass

media can also share information about innovations. Twitter, however, can serve as both of these

communication channels, guiding individuals through the information-gathering step in the

process (Seidel & Rogers, 2002). After the information stage, individuals will enter the

persuasion stage, where they form a good or bad attitude, or “organization of an individual’s

beliefs about an object that predisposes his or her actions” (Rogers, 2003, p. 174). In his

research, Rogers focused on the idea of a preventative innovation as one that would help an

unwanted future event from happening, such as birth control to control unwanted pregnancies. In

this same way, H1N1 vaccinations serve as preventative innovations to help stop the spread of

the swine flu influenza. Mass media and interpersonal communication continue to influence an

individual’s decision – they persuade a person to accept a preventative innovation like a flu shot.

Twitter also serves a purpose in this stage of the innovation-decision process by providing

additional information to help persuade potential users.

Next, individuals enter the decision stage of the innovation-decision process. At this

point, each person has to make a determination to try out the innovation – or not. Each individual


has a different threshold of information that must be acquired in order to make a decision about

an innovation (Dearing & Meyer, 2006). An individual will choose to adopt or reject an

innovation, sometimes trying out that new idea or tool on a partial basis (Rogers, 2003). In this

research project, the decision stage was represented by a determination whether or not to obtain

an H1N1 influenza vaccination. Each step of the research for this project was designed to follow

an individual Twitter user through the steps of the innovation-decision process and determine

whether or not the new method of communication helped that person reach the decision to

vaccinate or not.

A content analysis was undertaken to determine the information individuals and

organizations were sharing on Twitter about the H1N1 influenza pandemic in late 2009.

Individuals certainly communicated about the virus in great detail during the outbreak, but what

types of information were they sharing? A content analysis, where the researcher examines

textual information for patterns, was the tool chosen to find out main topics and themes for

H1N1 information on Twitter (Krippendorf, 2004). The analysis helped lead me to an answer for

the first research question – How is Twitter used as a communication channel for H1N1

information diffusion?

To ascertain the pertinent topics and communication themes, I analyzed 46,000 Tweets

that users posted about the H1N1 pandemic flu virus outbreak for prevalent themes. Through this

content analysis, which is the process of drawing similarities between information from different

sources (Krippendorf, 2004), I was able to identify three broad umbrella themes concerning the

H1N1 virus on Twitter – health information, uncertainty reduction, and misinformation. Each of

these three themes further divided into sub-themes – deaths, vaccinations, symptom

identification, and prevention. These three umbrella communication themes were chosen because


they shed light on the information stage portion of the innovation-decision process. Further

analysis, through surveys and interviews, helped determine how Twitter users progressed

through the next two stages of the process, persuasion and decision. While these Tweets can

communicate information in multiple ways – among them humor – the three main themes were

the most prevalent when the analysis was completed.

In this section, I begin by giving a broad view of the health-information-seeking

behaviors apparent in Tweets that focused on three topics – symptom identification, preventative

behaviors, and vaccination information. Next, I focus on misinformation and disinformation and

the three topics that feed into this theme – deaths, preventative behaviors, and symptoms of the

virus. Finally, I explore the theme of uncertainty reduction, and how information passed via

Twitter on both preventative measures and vaccinations contributed to the information-gathering

cycle individual users engaged in before entering the persuasion phase of the process, which was

charted through the survey phase of this research project.


Health-information-seeking Behaviors

Health-information themes focus on “the origin, treatment, symptoms, and other

biological perspectives associated with a disease” (Wang, Smith, & Worawongs, 2010). By

framing the H1N1 outbreak with medical or health information, communicators create a

perception of the virus as a health crisis and lead others to understand the virus outbreak in this

manner (Entman, 2007). Medical frames can allow communicators the ability to be more neutral

in sharing information, and thus, researchers can conclude that more organizations would post

health information-themed Tweets than would individuals (Clarke, 1991). According to Entman,

medical frames can also “introduce or raise the salience or apparent importance of certain ideas,

activating schemas that encourage target audiences to think, feel, and decide in a particular way”

(2007, p. 164). In effect, Tweets that deal with health information and are framed in a medical

manner help users in the first step of the innovation-decision process – the information stage. In

my research, I discovered that Twitter users posted both information-seeking and -giving posts

that fit into the health information theme. These Tweets point to the first step in the innovation-

decision process – the information stage.


Table 1

Tweets Relating to Information on H1N1

Categories of Information Example Tweets
Health information
Symptom identification Swine flu: symptoms so mild many
donʼt recall them
Preventative measures There is a lot more to preparing for and
preventing Swine Flu than just washing
your hands…
Vaccination Swine flu ʻshould be included in new
seasonal vaccineʼ – AFP

Misinformation and disinformation
Symptom misidentification Swine flu publicity means uptick in
OCD symptoms
Preventative measure confusion Human Protein That Can Prevent or
CURE H1N1 Swine Flu—Naturally!
Vaccination misinformation They are Injecting Mercury into
Children
Uncertainty reduction
Deaths Another swine flu death this time from
Bahraich
Prevention of spread Ordinary disposable surgical masks do
not protect health care workers from
swine flu
Safety and availability of Swine flu jab receives good response
vaccines

In addition, public health entities like the CDC use Twitter as a portion of their public health

information network, which was instituted “to make communication easy, to make information

accessible, and to make secure data exchange as swift and smooth as contemporary technology

will allow” (Peddecord et al., 2008; Baker, Freide & Moulton, 1995). These public entities work

to persuade users to embrace behavioral change, the true test of diffusion of an innovation, and

this behavior was evident from some health information Tweets as well (Peddecord et al, 2008).


Symptom Identification

The first sub-theme relating to health information found during the content analysis of

Tweets about H1N1 was symptom identification. It was a primary way users found both to seek

and share information on the virus. The sharing of health information ranged from users telling

their particular symptoms and seeking verification of those symptoms’ validity to complaining

about other people’s symptoms when they appeared in public ill with what appeared to be the

pandemic virus. A sample of symptom-related Tweets included:

• Feel crap. Reckon its #swineflu. How would ya know? A 2 wk cold that suddenly

gets worse with fever and weepy eyes...feel like death

• Swine flu: symptoms so mild many don’t recall them:

http://url4.eu/1nYyy.CurAbility.10512376142.59884668.en

• I am that coughing guy on the tube who you are looking at trying to determine if

that's swine flu or just a nasty cold. #innocent #swineflu

• 100.4 fever... who wants to bet what time i end up at the ER? #swineflu

• the fifth day the 2yrs old had fever hope it will stop tomorrow hate the #swineflu

• sudden onset of extreme nausea & fever. #swineflu ??

• Do you know the #symptoms of #H1N1 in #pets? http://is.gd/5pSyp #animals #cats

#dogs #swineflu #flu #family

• Dude in the office moaning and coughing like he has emphysema. #contagious

#swineflu

• On the train to london. Desperately trying not to sneeze on people and creating a

#swineflu stampede. Still would get carriage to myself.


• In times of #swineflu it's somehow irritating to see people that handle your food

cough or sneeze.

Tweets such as “Why would you go in public if you were non-stop coughing?!?” and

“looking at people with disgust when they sneeze” summed up what many individuals felt about

those who had either the regular flu or a more dangerous variant, yet refused to go to the doctor

or stay away from crowds. While these tweets may appear that individuals on Twitter are simply

complaining about inconsiderate sick people, perhaps their complaints were able to help other

sick individuals from entering society and spreading their illness.

Individuals not only sought information about symptoms as shown above. Organizations

were able to share pertinent information that would help individuals determine if they needed to

seek medical advice because of sickness. Tweets like “What is H1N1 swine influenza & What

are the symptoms?” followed with a link to a website containing more health information about

the flu were able to connect many with concise and precise data about flu symptoms, treatments

and prevention. Many health organizations were able to use the medium of Twitter not only to

share information about vaccination clinics, as seen above, but also to help guide sick individuals

to the proper treatment when necessary. In fact, the World Health Organization, one of the

recognized global leaders in the fight against the spread of H1N1 was able to use tweets like

“Swine Flu symptoms still widespread globally; statistics update by WHO” to share authoritative

information with the approximately 75,000 followers who watch the @whonews Twitter feed to

find out the latest information on H1N1 and other world health crises.

Information on Preventative Measures

Symptoms were not the only subject that individuals and organizations sought and shared

information about. Tweets such as “Morbid Obesity as a Risk Factor for Hospitalization and


Death due to 2009 H1N1 Virus” led readers to more health information about the spread of the

virus – combining data about the virus with more health information about preventative

measures. The obesity-focused tweet was particularly popular for retweeting, or the passing

along of information that individuals find to be important or particularly informative, as it was

passed along the Twitter information superhighway another seven times – within the three days

when Tweets were analyzed – beyond the initial sharing. The sharing of this pertinent

information shows particular interest in how different lifestyle choices figured into the possibility

of the virus’ spread. The obesity-centered H1N1 Tweet was but one example of how health

information was tied to preventative measures – both for individuals seeking help and those

trying to give help. The Tweets numbered in the hundreds in the dataset; here are a few

examples:

• RT @fffabulous: simple preventative ways to avoid the swine flu #swineflu

http://ow.ly/1kKOo (via @LoriGregory) #momspotting

• There is alot more to preparing for and preventing Swine Flu than just washing your

hands. .. http://tinyurl.com/ybxqq6d #swineflu

• Household Transmission Of H1N1 Influenza During Initial Outbreak Limited By

Preventive Behaviors http://mnt.to/3z4R #swineflu

• New blog post: : Preventing Common Cold and Flu with an Air Purifier in Your

Home http://bit.ly/cw7Zar #airpurifiers #cold #swineflu

• #H1N1 #SwineFlu #News Surgical masks effective in preventing H1N1:

http://url4.eu/21Cmt

• #swineflu Clean Door Handles Prevent Swine Flu | quebella.net: If one of them had

swine influenza you might have p... http://bit.ly/bnJrlD


• #swineflu H1N1 Swine Flu Prevention in the Dental Office | jellofart's blog:

Personnel providing direct patient ca... http://bit.ly/ayV0G8

• #SwineFlu Schools add Swine Flu Prevention 101 to their curriculum - WMBF

http://ow.ly/1689K4

• Do You Want To Keep Your Family Safe? Learn How To Prevent Swine Flu

http://tinyurl.com/yl37894 #swineflu

• #swineflu Alert swine influenza … You can prevent infection and a pandemic ...:

When most people think about the p... http://bit.ly/a8Fguc

Examples such as the ones focused on sharing preventative measures within the classroom and

the workplace are particularly strong illustrations of organizations utilizing the medium of

Twitter to share health information with the world in order to help stop the spread of the virus.

H1N1 Vaccination Information Sharing

Just as the swine flu Twitter stream featured hundreds of Tweets about both symptoms

and preventative measures, posts focused – especially well into the outbreak – into sharing and

searching for information on vaccinations. Information on H1N1 vaccination shared via Twitter

is wide-ranging, from particulars on where and when flu shots would be offered to the possible

side effects of H1N1 vaccinations. These health-information Tweets are focused on the

information-sharing side of the equation, but one can also see a number of posts seeking

information about the safety of vaccinations.

One of the most important uses of the medium during the height of the outbreak,

however, was the use of Twitter to share information on vaccine clinics. Thousands of tweets

such as “Free H1N1 vaccine available Sunday at Pensacola locations” allowed residents of

certain areas the opportunity to find pertinent health information as well as alleviate uncertainty


about the virus and its prevention. In addition, organizations whose job was to ensure that

vaccines were administered were able to pass their message along in much the same way as they

would use mass media. When individual Twitter users reposted information on clinics through

retweets, the message from health organizations was simply communicated to a larger audience

through the mass medium. Indeed, sharing information via Twitter on vaccination clinics became

a new form of mass media, albeit with an interpersonal communication twist, and a valuable

weapon for those fighting the spread of the virus. A sample of vaccination-related Tweets

included:

• Swine flu vaccine producers reach last trial stage in India - fnbnews.com

(http://cli.gs/uqb3r) #swineflu #H1N1

• Commentary on potential CDC pandemic #H1N1 vaccine mismatches #swineflu

http://bit.ly/9cMc9l

• #SwineFlu #H1N1 #News Get your children vaccinated against swine flu:

http://url4.eu/1no3F

• Get your children #vaccinated against #swineflu - This Is Hampshire.net :

http://bit.ly/aJOIJl

• Contra Costa County Offering New #SwineFlu Clinics - CBS 5 : http://bit.ly/bK9K5q

• #SwineFlu #H1N1 #News Scottish GPs hit swine flu vaccination targets:

http://url4.eu/1o5kQ

• RT @intouchwme RT @hniman: Comments on #H1N1 #vaccine failure in

#Wyoming & D225G role #swineflu http://bit.ly/aX2o5S :[

• Majority of 'at risk' Islanders did not bother with the #swineflu jab - Isle of Man

Today : http://bit.ly/arZWuc


• CSL Profit Beats Estimates on Swine Flu Vaccine Sales http://bit.ly/amWg5F

#swineflu #vaccine

• Swine flu 'should be included in new seasonal vaccine' - AFP (http://cli.gs/L6Njs)

#swineflu #H1N1

Throughout the spread of the virus, individuals and organizations shared data on

vaccination clinics as well as how the vaccine was perceived in different areas of the world. This

information sharing was valuable to those who might not obtain information in traditional ways,

particularly those who were in a high-risk category but unable to obtain information from

traditional mass media or interpersonal connections.


Misinformation and Disinformation

While Twitter certainly allows legitimate organizations and individuals to pass along

information related to H1N1, its symptoms, prevention, and vaccinations, the medium also

allows individuals and groups the opportunity to pass along false information. This data sharing

is not always intentionally malignant. However, disinformation can negatively impact

individuals’ ways of dealing with the virus during times of crisis. In addition, misinformation can

cause individuals to avoid life-saving measures because there is a vacuum of correct information.

In the absence of data that could influence users to embrace the innovation of immunization or

preventative measures, disinformation and misinformation can cause real issues for health-care

providers. In short, the use of misinformation can prevent individuals from reaching the second

step of the innovation-decision process, persuasion, which Rogers (2003) states is the stage in the

process where an individual forms a positive or negative opinion of an innovation. In this case,

individuals needed to form a positive opinion of the H1N1 vaccination and prevention

techniques in order to practice them.

From uncertainty, which will be discussed in the following section, frequently comes a

spread of misinformation. A lack of information in a crisis creates a vacuum that communicators

are driven to fill (Ulmer et al., 2007). For instance, during the October 26, 2009, shooting on the

University of Central Arkansas campus, individuals were driven to blogs, Twitter, and other

CMC tools in order to find out more information. The quickest individuals to respond to

uncertainty with information are frequently not the ones with correct information. The spread of

misinformation could easily be seen in the beginning of the H1N1 outbreak by the numerous

mentions of staying away from pork or avoiding travel to certain areas of the world – both

Tweets that were carried around the world but that had no actual basis in fact. In this case,


however, unlike scholars had earlier noted, misinformation and disinformation were not passed

along because of an ill intent or a desire to persuade (Hatchen & Scotton, 2007). Instead,

individuals were trying to fill an overwhelming information vacuum with their Tweets.

Symptom (Mis)identification

Perhaps the most misinformation on H1N1 that was shared via Twitter concerned the

identification of symptoms related to the spread of the virus. According to the Centers for

Disease Control and Prevention (2010a), H1N1 flu symptoms included fever, cough, sore throat,

runny or stuffy nose, body aches, headache, chills and fatigue. However, during the height of the

virus discussion, Tweeters attributed everything from hot hands to pale skin to the onset of the

virus. No doubt many individuals were confused if they were unable to verify information about

symptoms of the virus with expert sources. Posts that featured misinformation about H1N1

symptoms differed from posts that featured health information-seeking and -sharing because the

individuals who broadcast symptom misinformation listed incorrect symptoms. In addition, these

Tweets with misinformation focused on missing work or school or taking advantage of one’s

apparent symptoms.

In the course of the three days targeted for content analysis, the tweet “I look like a

#zombie really feel awfull, … maybe i have the #swineflu” appeared over 120 times in the

analyzed tweets. The individual user who originally sent this tweet may have known that H1N1

symptoms include fever, aches, and fatigue, but he or she may not have known that a simple

complaint would spread so rapidly (CDC, 2009a). And while this Twitter user did not spread

completely false information, his or her approach certainly raised red flags for those of her

followers who were concerned about the spread of the disease and their contact with him or her.

Individuals also expressed concern when actress Lindsey Lohan tweeted about being achy


(“Lindsay’s tweet sparks,” 2010). Her offhand remark sent shockwaves through news media as

well as the Twitter universe, with a number of tweets such as “Lohan sparks #swineflu fears with

‘achey’ tweet” being sent after her original message. Other Tweets that spread misinformation

about symptoms included:

• Swine flu publicity means uptick in OCD symptoms - Gloucester Daily Times: All

those swine flu warnin.. http://bit.ly/7IzOUl #swineflu

• I'm almost certain that with the amount of coughin sneezing and blowing of the nose

going on in this train car somebody has the #swineflu

• Speaking at Harvard: - Salon: randomly shouting -Swine Flu- at anyone who

coughed.) I experienced my .. http://bit.ly/7asewC #swineflu

• Going down hill rapidly I hope this isn't swineflu #swineflu symptoms

• #nevertrust a person that says “my allergies actin up” a cough a sneeze or a runny

nose lasting more than 3 days = #swineflu

• #nevertrust someone thats been coughing/sneezing and wants to give u daps or if its a

female give u a hug...#swineflu

• #nevertrust a person that's too touchy feely especially if you don't them #swineflu

#H1N1

• S/O 2 Me Coughing all over the place acting like I got the #SwineFlu ... Lol can we

say day off #WithPAY Hello Brooklyn :-) !!!!

Confusion on Preventative Measures

Alongside many Tweets about symptoms that contained misinformation and

disinformation, there were a large number of Tweets that featured dubious data on preventative

measures. Most of the tweets aimed at preventative measures appeared to be designed to sell


some specific tool or information about the spread of the virus. And for almost every one tweet

that tried to sell something, there was a tweet designed to debunk the misinformation that was

passed around. For instance, for every “Should I wear a flu mask to protect myself from swine

flu?” tweet accompanied by a link to a medical supplies warehouse, there was a “Garlic Sellers

Cashing In On Flu Rumors (That Garlic Prevents Swine Flu” to dispel myths. In this way,

Twitter became a self-correcting network during the H1N1 outbreak. Individuals were able to

find information – both correct and incorrect – about the virus, and they were able to react

appropriately when choosing preventative measures. A few of the preventative measure Tweets

were:

• Preventing Illness- Including the Flu! | www.healthyindoorairllc.com http://ow.ly/196RZ

#h1n1 #health #swineflu #flu

• #SwineFlu Human Protein That Can Prevent or CURE H1N1 Swine Flu--Naturally! -

Examiner.com http://ow.ly/16b9Kp

• Aurelie with the bear mask : http://bit.ly/7yDqLA #mask #swineflu #bear #H1N1

#vaccine #flu #protection #pimp #prevent

• Tonight I'm trying a humidifier some voo-doo and any other magical snake oil I can find.

#bedtimesucks with my cough from the #swineflu!

• Epigallocatechin Gallate (EGCg) in Green Tea Confirmed to Prevent ... - Yahoo Finance:

Influenza viru.. http://bit.ly/8TCwY1 #swineflu

• #SwineFlu Prevention Tip 34: This Christmas don't open any presents and avoid all

contact with loved ones to keep from getting sick.

Tweets aimed at helping individuals prevent the spread of the swine flu virus ranged from

the innocuous “Here are 10 swine flu prevention tips” to the inflammatory “Think schools should


be closed to prevent #SwineFlu outbreaks?” While the first tweet was clearly information-

sending and designed to help individuals, the second tweet on prevention was information-

seeking and appeared to be designed to spark a discussion on the virus. Especially during the

height of the virus spread, such discussions could quickly go awry, resulting in arguments over

the safety of everything in the brave, new world that contained such horrors as H1N1.

Vaccination (Mis)information

While organizations and individuals worked to share the correct and official information

concerning vaccination programs surrounding the H1N1 outbreak, a great deal of what could be

perceived as misinformation was also shared about vaccines and their safety. These posts – ones

that shared incorrect information or showed that the user was uninformed about the vaccine –

disagreed with public health policy that advocated the vaccination of most individuals (Centers

for Disease Control and Prevention, 2009b). Side effects resulting from a vaccination were the

most common types of posts that featured misinformation. These misinformative vaccination

posts were different from other Tweets focused on vaccinations because they listed a host of

negative symptoms that were different from those listed in CDC materials. The CDC listed the

most common vaccination side effects as soreness, redness, and swelling where the shot was

given (2009b). However, Twitter users listed a litany of possible negative effects from the

vaccination as well as questions about the vaccinations’ efficacy and safety; a sample of those

Tweets included:

• My arm hurts and I feel weak and milky today. Poor me.

#symptomsfromtheswinefluvaccine #swineflu

• If these are swineflu #vaccine symptoms I do not want to have the #swineflu.

• #Swineflu jabs may be wasted - The Age : http://bit.ly/atbTFG


• Live #Radio #Today 3PM EST They Are Injecting #Mercury into Children

http://bit.ly/7xot3i #H1N1 #Swineflu #novacs @mayereisenstein

• #SwineFlu Severity warning over low uptake of swine flu jab - The Standard

http://ow.ly/169yeF

• Vulnerable patients shunning #swineflu #vaccine GPs warn - Telegraph.co.uk :

http://bit.ly/44yKGA

• No soreness in my arm but am feeling the first side-effect of the vaccine: lethargy

#swineflu


Uncertainty Reduction

In addition to communicating via Twitter on H1N1 for health information and finding

information, misinformation, and disinformation, users of the microblogging service were able to

use Twitter to alleviate uncertainty. Frequently, information was shared to dissuade individuals

from believing the misinformation and disinformation that were passed along through Twitter at

the beginning of the outbreak. When Tweets were examined for content, a large number surfaced

that related to the uncertainty that individuals felt in the context of a worldwide health crisis.

Ulmer, Sellnow, and Seeger (2007) define a crisis as an exceptional event, something that results

in a certain amount of surprise and threat for individuals as well as a situation that requires a

short response time for communication of answers or assistance. In fact, the less individuals

know about a given situation, the more uncertain they are and the more they search out

appropriate information to make themselves comfortable with a situation (Littlejohn & Foss,

2008).

The H1N1 outbreak in 2009 is a pertinent example of a health crisis; a large amount of

uncertainty resulted for individuals who felt they were in danger of contracting the virus. The

unique pattern of deaths that resulted from the virus (Figure 2), with a large number of young

adults dying from the disease, caused even more uncertainty for those who would normally

consider themselves safe from such an infection. As a result, a large number of Tweets were

posted that showed individuals’ concerns with deaths as well as a number of Tweets that were

focused on finding information about symptoms and vaccination sites. Though these sub-themes

repeat the themes discussed in earlier sections, an analysis helped discern that individual users

and organizations are clearly concerned with alleviating uncertainty through CMC. As a

secondary result of the effective use of Twitter to remove uncertainty, organizations were able to


bring individuals to the tipping point of information, helping them enter the persuasion phase of

the innovation-decision process (Figure 6).

Figure 6. Representation of the tweeting processes Involved in persuasion for decision
making in H1N1 vaccination. Adapted from Ev Rogersʼ Diffusion of Innovations. 

Information about Deaths

On each of the three key analysis dates, a number of Tweets appear detailing death counts

in various countries, and these “death Tweets” are directly tied to the uncertainty-reduction

theme. While individuals may not like hearing about the number of deaths throughout the world

because of H1N1, it was certainly better for users to know the truth than guess about the

possibilities. Observers were able to watch the spread of the virus throughout the world via

Twitter. In addition to sharing information on numbers and the virus’ spread, these focused


Tweets allow a view into the effect of the virus on health-care workers. For instance, a tweet

stating “Moldova: 15 H1N1 deaths incl doctor infected from patient” reminds observers that

those who are entrusted with treating patients are also in danger of contracting H1N1. Other

“death Tweets” included:

• #SwineFlu Another swine flu death this time from Bahraich - Indian Express

http://ow.ly/16fSWn

• CDC Offers Latest Estimates of H1N1 Toll http://bit.ly/9It0wL #h1n1 #swineflu (via

@Breaking_h1n1)

• Medics meet to discuss #swineflu death - Daily Echo : http://bit.ly/apIpWu

• US #h1n1 #swineflu figures for last year: up to 86m infections 12000 deaths

http://is.gd/aJtN2

• Swine Flu Death Toll in India goes up to 1415 - BreakingNewsOnline.

(http://cli.gs/Tyq7L) #swineflu #H1N1

• 2 some-more deaths in Oklahoma uncover H1N1-flu risk remains

http://tinyurl.com/ybfuvvk #swineflu #hongkong

• Global #swineflu death toll creeps towards 16000: #WHO - Victoria Times Colonist :

http://bit.ly/b8R7L6

Spread of H1N1 Prevention Information

In addition to sharing H1N1 death tolls or seeking information on them, individuals who

used the social media microblogging service sought and shared information on their symptoms.

Organizations also used the medium to share data about how to prevent the spread of the virus.

These tweets went much further than the health information recommendations for hand washing

and covering the nose and mouth when coughing and sneezing, however. Many groups –


companies that were probably marketing items designed to play on individual fear about H1N1

spread – used the service to tout their wares as the best way to keep from getting swine flu. By

using Twitter in this way, these companies not only shared health information, they also took

advantage of individuals’ uncertainty about the H1N1 virus and its spread. Examples of these

Tweets designed to relieve uncertainty about prevention of the virus include:

• #swineflu Swine Flu- How Can I Optimize My Immune System? | Swine Flu: Swine

flu or swine influenza was first http://url4.eu/1nLT0

• Swine Flu Protection. Flu Masks Surface Disinfectants. Be prepared. Protect yourself

today. http://tinyurl.com/ydocc6f #swineflu

• Ordinary disposable surgical masks do not protect health care workers from swine

flu. http://tinyurl.com/yco97jd #swineflu

• Study links lack of paid sick days to spread of Swine Flu - Bristol Press

(http://cli.gs/sa5Xy) #swineflu #H1N1

• N95 masks are the only masks that provide protection from the swine flu virus.

http://tinyurl.com/y9sruou #swineflu

• Swine Flu: Know what to do if a family member gets sick http://tinyurl.com/ycewerh

#swineflu

Safety and Availability of Vaccines

Finally, individuals and groups used the medium of Twitter to communicate information

about vaccinations – their safety and availability – in order to alleviate uncertainty within the

general population. The vaccine talk received much attention in each of the areas covered by

H1N1 themes in this content analysis. A sample of the information-seeking and -supplying

Tweets that focused on vaccinations are:


• #SwineFlu #H1N1 #News Swine flu jab receives good response:

http://url4.eu/1nPLY

• Commentary on potential CDC pandemic #H1N1 vaccine mismatches #swineflu

http://bit.ly/9cMc9l

• U.S. may end up discarding unused #swineflu vaccine http://tinyurl.com/yk9b97b

#tcot #tlot

• #H1N1 #SwineFlu #News 500000 people vaccinated against A/H1N1 flu in Mexican

capital: http://url4.eu/1QdPl

• #H1N1 #SwineFlu #News 34300 doses of imported H1N1 vaccine arrive in Mumbai:

http://url4.eu/1p07Z

• #H1N1 #SwineFlu #News Azerbaijani health minister: No complications in A/H1N1

vaccination in Azerbaijan: http://url4.eu/1RH3R

The concept of using information to promote particular health-related behaviors is not a

new one, though scholars have recently become more interested in health information as an area

for study. The use of entertainment media in particular has become more popular in recent years,

as scientists and doctors attempt to use friendly methods of sharing health information with the

individuals who are most affected by particular diseases and syndromes (Peddecord et al., 2008;

Singhal, Njogu, Bouman, & Elias, 2006). From birth control to preventing HIV and AIDS to

encouraging vaccinations, communicators frequently use a variety of mass media and

entertainment venues to share information with audiences.

The use of Twitter to talk about the H1N1 outbreak is no different. In fact, according to a

post from the computer-mediated communication tool, “#swineflu and #H1N1 were two of the

most popular hashtags in all of 2009. #whenswineflew.” Twitter can also help individuals move


from the first step of the innovation-decision process – information acquisition – to the second

step – persuasion. In the second section of my research, I worked to discern how much individual

Twitter users paid attention to their feeds when it came to information on H1N1.


Results – Surveying the Users

Following the content analysis of Tweets about the H1N1 outbreak, an online survey was

conducted to find out basic information about Twitter users’ social media habits as well as the

amount of influence that Twitter has on their off-line behaviors. Some general demographic

information from Arbitron-Edison Research on Twitter users in 2010 is helpful for understanding

how individuals use the communication tool (See Table 2). Overall, more women (53 percent)

than men (47 percent) use the tool. A majority of users are white (51 percent), followed by black

(24 percent), Hispanic (17 percent), and Asian (3 percent). A third of users fall in the 25-34 year

old age range, while the next largest groups are 35-44 year olds (19 percent) and 12-17 year olds

(18 percent).

The average Twitter user fits a demographic profile that conforms to Rogers’ definition

of opinion leadership. These individuals are exposed to more mass media, are involved with

more groups than their immediate social group, are more innovative, and are accessible to many

individuals – sharing their opinions with many (Rogers, 2003). According to Arbitron surveys,

individuals who utilize the microblogging service fit this description well. More Twitter users

(47 percent) record an average household income over $50,000 per year as compared to the total

population (33 percent with incomes over $50,000 per year) (Edison Research, 2010). Twitter

users are well-educated, with 63 percent of the population having a four-year college degree or

more. Only 40 percent of the general population has a college degree or higher (Edison

Research, 2010). These users are also regular cell phone and computer users, and they spend

more time on social networking that those who choose not to use Twitter (Saint, 2010). In

addition, forty percent of Twitter users have three or more computers in their homes (Saint,

2010).


Table 2

Portrait of Twitter Users

Whoʼs Using Twitter

Sex

Men 47%

Women 53%

Race

White (Non-Hispanic) 51%

Black (Non-Hispanic) 24%

Hispanic 17%

Asian 3%

Other 5%

Age

12-17 18%

18-24 11%

25-34 33%

35-44 19%

45-54 12%

55+ 7%

Source: Edison Research

According to Rubin, Rubin, and Piele (2005), survey research is counted as people- or

behavior-oriented research, which centers on the actions and reactions of individuals and can

include “self-report of attitudes and behaviors via survey questionnaires, observations of other

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