Computers in Human Behavior 29 (2013) 1641–1648
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Computers in Human Behavior journal homepage: www.elsevier.com/locate/comphumbeh
Does Twitter motivate involvement in politics? Tweeting, opinion leadership, and political engagement Chang Sup Park ⇑ College of Mass Communication and Media Arts, Southern Illinois University Carbondale, United States
a r t i c l e
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Article history: Available online 8 March 2013 Keywords: Twitter Opinion leadership Uses and gratifications Political discussion Political participation
a b s t r a c t This paper, in order to deepen our understanding of the role of opinion leadership on Twitter, the world’s largest microblogging service, has investigated the interrelationships between opinion leadership, Twitter use motivations, and political engagement. It finds that Twitter opinion leaders have higher motivations of information seeking, mobilization, and public expression than nonleaders. It has also been found that mobilization and public-expression motivations mediate the association between perceived opinion leadership and Twitter use frequency. Most importantly, this study finds that Twitter opinion leadership makes a significant contribution to individuals’ involvement in political processes, while Twitter use itself or media use motivation does not necessarily help individuals’ political engagement. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction Social media have attracted much scholarly attention for their potential in enhancing political engagement of individual citizens (Castells, 2007; Gaffney, 2010; Tumasjan, Sprenger, Sandner, & Welpe, 2011). Among a multitude of social media, Twitter, which is the world’s largest microblogging service and third largest social network site behind Facebook and YouTube (Barnett, 2011; Parmalee & Bichard, 2012), has particular potential to be a strong force in adding to political discourse due to its open, horizontal, and broadly-networked architecture. Unlike Facebook, which defaults to restricted, in-network exposure to other users’ posts, Twitter posts are disseminated publicly and can be easily viewed by all users. The open system of Twitter creates a venue for users to respond to other users, thereby making it a vibrant forum for public discourse (Kim, 2011). Despite the great potential, little is known as to how Twitter works as a motivator of political engagement. This study examines the mechanism in which Twitter influences individuals’ engagement in political processes. To this end, the present study pays a particular attention to the role of ‘opinion leadership,’ which is expected to motivate Twitter users to get involved in political activities. We see various anecdotes that using the information and communication technologies (ICTs) for political awareness is boosted by ‘opinion leaders.’ In a similar vein, Twitter opinion leaders are presumed to have the ability to encourage individuals to get involved in political processes through robust interpersonal dis-
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cussion and exchange of ideas. The enhanced capabilities of Twitter such as reaching diverse people simultaneously and garnering wide resources at a short time may help individual opinion leaders to enhance their political awareness, mobilize supporters, and coordinate collective actions. Traditionally, opinion leaders are characterized by higher social status, gregariousness, and more social contacts. They tend to be more highly exposed to news media content than nonleaders. However, some of traditional opinion leadership concept may not hold true in Twitter environment. For instance, on Twitter, social status does not matter much. Presumably expertise is a much more important requirement for an opinion leader on Twitter than socioeconomic status. This presumption is corroborated by Chang and Kim (2011). In their analysis of South Korean Twitter users, they found that 80% among the most popular 1% tweet messages were created by ordinary individual users instead of traditional opinion leaders such as politicians, professors. Unlike traditional opinion leaders, the opinion leaders on Twitter tend to play a role as a new type of agenda generator or news disseminator, irrespective of their social, economic, or political standing. That is, Twitter provides any user with opportunities to become an opinion leader, if only the user could produce noticeable information to attract public attention (Hwang & Shim, 2010). The present study focuses on the unique characteristics of Twitter opinion leaders and explores their plausible impacts on political engagement. The rest of the paper is organized as follows: First, it provides a review of previous studies on opinion leadership, Twitter use motivations, and the political potential of Twitter. Then, findings from an online survey conducted with 439 university students in the United States are analyzed. Lastly, implications of the survey results are articulated.
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2. Literature review 2.1. Traditional opinion leadership Originally opinion leaders were defined as ‘‘the individuals who were likely to influence other persons in their immediate environment’’ (Katz & Lazarsfeld, 1955, p. 3). They come up with new information, thoughts, and opinions, then disseminate them to the general public. They tend to become an influential node by grasping the most representative opinions in society (Song, Chi, Hino, & Tseng, 2007). In other words, opinion leaders refer to people who influence opinions, attitudes, beliefs, motivations, and behaviors of others in a desired way with relative frequency (Hellevik & Bjorklund, 1991; Mowen, 1990; Rogers, 1983). The construct of opinion leadership has its roots in the voting behavior study conducted by Lazarsfeld, Berelson, and Gaudet (1948). They proposed the two-step flow theory that ideas flow from the mass media to opinion leaders and then to the general public. According to the theory, opinion leaders tend to be more highly exposed to the news media content than are nonleaders. They also tend to process information more efficiently than general people. Because opinion leaders are more interested in public issues and better informed than nonleaders, they often become the main source of impact over the public. The two-step flow theory has evolved into the diffusion of innovation approach – the theory about how innovations become spread throughout a social system. The diffusion theory finds almost similar characteristics of opinion leaders as the two-step flow model. According to the innovation diffusion theory, opinion leaders (1) are more exposed to all forms of external communication, (2) have somewhat higher socioeconomic status, (3) are more innovative, and (4) are at the middle of interpersonal communication networks (Rogers, 1983). To date, the original conceptualization of opinion leadership remains almost unchanged. Opinion leaders often have higher levels of interest, knowledge, and recognition about social issues than non-leaders (Weinmann, 1994). Opinion leaders tend to view themselves as the pioneers of social trends, and early adopters of innovations (Rogers, 1995; Summers, 1970). They tend to perceive themselves as intelligent and independent enough to form personal judgments about public issues that they can share with others (Chan & Misra, 1990). Opinion leaders have usually higher socio-economic status and education than others in their social system. They are also more likely to be ‘‘interconnected’’ than opinion followers (Rogers, 1983). Through these networks of relations, opinion leaders can exert significant impacts on others.
2.2. Opinion leadership on Twitter Twitter can be a fruitful soil for opinion leadership formation. It provides an easy communication tool that enables any individual user to send and share information about their activities, opinions, and status (Honeycutt & Herring, 2009). Updates or posts are made by succinctly describing one’s current status within a limit of 140 characters. Due to the advantage of brief messages, Twitter lowers users’ requirement of time and thought investment for content generation, facilitating communication flexibility, interactivity, and speed. Users are able to post links to news stories, share and discuss those topics instantaneously. Considering such peculiar features of Twitter, this study presumes that the opinion leadership on Twitter would be a little different from the traditional opinion leadership. For instance, opinion leaders on Twitter tend to depend more on their own expertise and perspectives rather than on their social positions. In other words, the level of visible education or established social
standing may not matter much in acting as an opinion leader on Twitter. Instead, the influential power of opinion leaders on Twitter is expected to derive from their informal status as individuals who are highly ‘‘connected.’’ That is, networks that are broader than those of traditional opinion leaders may be one of the important traits of Twitter opinion leaders. According to a social media monitoring company Beevolve. (2012), Twitter users on average have 208 followers and follow 102 users themselves, which is amazing considering that the everyday relationship boundary of ordinary people. Furthermore, opinion leaders on Twitter are more likely to be involved in a ‘multi-step flow’ process, as opposed to the traditional ‘two-step flow’ process introduced by Katz and Lazarsfeld (1955). While the two-step flow is ‘‘a process of the moving of information from the media to opinion leaders, and influence moving from opinion leaders to their followers’’ (Burt, 1999, p. 38), a multi-step flow indicates that a message is distributed through a myriad of intermediary channels. On Twitter those who are wellconnected play a more potent role in creating and distributing information through a multi-step flow than those with less connection. 2.3. Twitter opinion leaders and media use motivations Twitter is not only a means to expand interpersonal communication, but also a tool of exchange and discussion of current issues that occur in a society. It seems that Twitter opinion leaders are more likely to participate in obtaining, distributing, or commenting on information. What leads Twitter opinion leaders to such behavior? Maybe they have some motivations to use Twitter in such a way. This study investigates the major motivations of Twitter opinion leaders, based on the uses and gratifications (U&G) theory. The U&G theory is basically concerned with how different individuals use the media in pursuit of their wants and needs (Raacke & Bonds-Raacke, 2008). This approach is based on the notion that a medium cannot influence an individual unless that person has some demands for that medium or its messages (Rubin, 2002). That is, one of the important assumptions of the U&G theory is that an ‘‘active’’ audience makes conscious decisions when she or he tries to use media content (Rayburn, 1996). Although the U&G approach has been criticized on several grounds such as a failure to consider audiences’ perceptions of media content, a vague conceptual framework, and a lack of precision in major concepts (e.g., Carey & Kreiling, 1974; Elliot, 1974; Swanson, 1977), this study employs the U&G approach as a conceptual framework to understand an aspect of Twitter opinion leadership. Previous studies suggested various motivations for using Twitter as follows: social participation through information exchange, forming a follower group based on interaction, information seeking and distribution, everyday conversation, checking public opinion, entertainment, and private expression (Hwang & Shim, 2010; Java, Finin, Song, & Tseng, 2007; Mischaud, 2007; Zhao & Rosson, 2009). This research, on the basis of prior studies’ findings and the nature of public-forum function of Twitter, focuses on the following three motivation categories: information seeking, mobilization, and public expression. The three motivations are all related to surveillance needs of individuals. A body of literature reports that opinion leadership has a close association with surveillance motivation (Chan & Misra, 1990; Levy, 1978). Therefore, it is hypothesized: H1a. Perceived opinion leadership of individual Twitter users will have a positive relationship with information-seeking motivation.
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H1b. Perceived opinion leadership of individual Twitter users will have a positive relationship with mobilization motivation. H1c. Perceived opinion leadership of individual Twitter users will have a positive relationship with public-expression motivation. Even though it seems that opinion leadership of individuals bears a positive relationship with Twitter use, it is not certain that opinion leadership directly affects Twitter use. As emphasized above, Twitter, because of its unique architecture and traits, offers an opportunity for any individual to function as an opinion leader regardless of the social status or situation of the user. Put differently, opinion leaders in terms of traditional perspective may not play the same role on Twitter, if they do have few, if any, motives to use Twitter. This reasoning can be indirectly supported by our daily observations that younger people who tend to depend on Twitter to get information play a more significant role in disseminating important social agenda than older people who do not have such motivations (Hankyoreh, 2 January, 2012). In this vein, this study hypothesizes that the motivations for Twitter use will play a significant role, as a mediating variable between traditional opinion leadership and Twitter use. According to Baron and Kenny (1986), a mediating relationship helps us understand how and why certain effects occur. H2. perceived opinion leadership of individual Twitter users will have a positive relationship with Twitter use frequency.
H3. Twitter use motivations will mediate the association between perceived opinion leadership and Twitter use frequency. 2.4. Twitter opinion leadership and media consumption Do opinion leaders on Twitter spend more time on the media than nonleaders? Concerning opinion leaders’ media use, results of previous research are mixed. Some studies found opinion leaders tend to be heavy consumers of the mass media (Rogers, 1983; Summers, 1970). Opinion leaders are more exposed to and responsive to new information and ideas, usually through various mass media (Keller & Berry, 2003; Shah & Scheufele, 2006). According to Katz and Lazarsfeld (1955), opinion leaders use more media and are more influenced by it than others. Katz (1957) found that opinion leaders are ‘‘considerably more exposed to the radio, to the newspapers, and to magazines’’ (p. 64). According to Levy, as opinion leadership increased, individuals claimed that their use of television news for information and opinion acquisition also increased. Recently, opinion leaders are being driven beyond the traditional media to seek more contexts and perspectives of news on social or political issues utilizing multiple media channels (Lee & Kim, 2012). For instance, the Internet provides opinion leaders with an innovative tool, so that they can learn about numerous social and political issues and disseminate information without temporal and spatial restraints. Importantly, the Internet, an instrument for learning about politics and involving in public life, is often considered as a supplement to traditional news sources (Bimber, 1998; Hardy & Scheufele, 2005; Shah, Cho, Eveland, & Kwak, 2005). On the other hand, some scholars argue that opinion leaders do not use media more than nonleaders do (Levy, 1978; Lin, 1973; Robinson, 1976). Chan and Misra (1990) found no significant difference in print media exposure between opinion leaders and nonleaders. Levy (1978) also reported that public-affairs opinion leaders do not show markedly higher rates of mass media exposure than those not defined as leaders, particularly with television news.
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Considering that Twitter opinion leaders are expected to depend on more on their own expertise than other sources as mentioned above, it is possible that opinion leadership on Twitter is not significantly related to media consumption. But based on the previous literature, this study asks: RQ1: In what way is perceived opinion leadership of Twitter users related to media use?
2.5. Twitter opinion leadership and political engagement Political participation has long been considered as an essential characteristic of democracy. Verba, Schlozman, and Brady (1995) defined political participation as a behavior that seeks to influence government actions by affecting public policy decision making. It includes traditional activities such as voting, working for political campaigns, donating money to candidates, and displaying political bumper stickers. It also includes conventional behaviors such as protesting, boycotting, and buying products for political reasons. Conway (1985) conceptualized political participation as the activities that citizens perform in order to influence different levels of the government, such as its structure, policies, or officials. In short, political participation can be referred to as one’s intent to influence government or public actions through diverse voluntary involvement. Whether opinion leadership is associated with political participation has been an important question among scholars. A number of studies found that opinion leaders are politically aware and active (Black, 1982; Keller & Berry, 2003; Kingdon, 1970; Robinson, 1976). Opinion leaders tend to show a higher level of involvement in public or political activities. They are more likely than nonleaders to engage in political behavior such as contributing to a party candidate, voting, and attending political meetings (Black, 1982; Kingdon, 1970). Further, opinion leaders have a tendency to direct fellow citizens’ reactions to political issues by setting and suggesting specific agenda (Brosius & Weimann, 1996; Weimann & Brosius, 1994). A similar reasoning can be applied to Twitter opinion leaders. It is well documented that opinion leaders tend to use ICTS in order to help inform, involve, and mobilize citizens for collective action (Dahlberg, 2001; Norris, 2001). Kavanaugh, Zin, and Carroll (2006) have found that blog opinion leaders are more likely to have higher political interest, engage in political activities, and involve in community collective actions. Likewise, Twitter opinion leaders are predicted to engage in the political process more frequently than nonleaders. In addition to the role of Twitter opinion leadership in the political process, this study investigates whether the motivations to use Twitter lead to increased political engagement. Scores of past studies have demonstrated that political motivation fosters political engagement (Rokeach, 1973; Triandis, 1995). Inglehart (1990) has argued that the rising level of cognitive mobilization, such as political interest is associated with higher levels of political engagement. Funk (1998) has noted that increased societal interest contributes to ‘‘efforts to solve community problems and giving money to charities’’ (p. 610). Many studies found that informational uses of the media contribute to civic and political engagement (Chaffee, 1982; McLeod, Scheufele, & Moy, 1999; Norris, 1996; Shah & Scheufele, 2006; Shah et al., 2005). Individuals who make use of news content are more likely to become interested in politics in order to satisfy the desire to stay informed. Building on the prior research, this study expects that both Twitter opinion leadership and the three motivations will be positively associated with political discussion and political participation.
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H4. Perceived opinion leadership on Twitter will be a significant predictor of political talk and political participation.
H5a. Information seeking motivation of Twitter opinion leaders will be a significant predictor of political talk and political participation.
H5b. Mobilization motivation of Twitter opinion leaders will be a significant predictor of political talk and political participation. H5c. Public expression motivation of Twitter opinion leaders will be will be a significant predictor of political talk and political participation.
3. Method 3.1. Data collection Data for this study were collected by a Web-based survey, which was conducted from December 10, 2011, to January 10, 2012, at a large public university located in the United States. Given that nearly three quarters (73.7%) of all Twitter users are between the age of 15 and 25 (Beevolve, 2012), university students can be a good venue to recruit survey participants. A random sample of 3000 undergraduate and graduate students was retrieved from the university registrar’s office. Then, email invitations with a short description of the study were sent to them. In order to limit the participation to Twitter users, a preliminary question which asked if they use Twitter or not was given first before the actual survey questions followed. Among the total 1358 students who clicked the requested survey link, 801 students dropped at this stage, leaving 557 participants. After the examination of the eligibility requirement of this study (whether or not a participant has a Twitter account), 118 responses were discarded. Finally, the present study used 439 responses for the analysis. According to the Pew Internet & American Life Project (2012), the proportion of Twitter adoption of the 18–24 age group is 31% as of February 2012, and that of the 25–34 age group is 17%. Considering that the adoption rate of Twitter among young adults is increasing drastically every year, the proportion of Twitter use of this study’s participants (439/1358 = 32.33%) is not much different from the average Twitter use pattern in the US. 3.2. Measurement Perceived opinion leadership. The measurement of opinion leadership can be done with various methods such as celebrities method, self selection, self identification, staff selection, positional approach, judges’ ratings, expert identification, snowball method, sample sociometric, and sociometric (Valente & Pumpuang, 2007). Each method has its own advantages as well as disadvantages. Among various methods, this study capitalizes on the self-identification method. This method requests individuals to fill out a survey measuring their perceptions of their own opinion leadership (Childers, 1986; Rogers & Cartano, 1962; Weimann, 1991). Those who respond affirmatively or score the highest on the scale are considered as opinion leaders (Hamilton, 1971). The major drawback of the self-identification method is that respondents may bias responses in a certain direction either intentionally or unintentionally because the measurement is based only on individual self-report. However, this technique
can be very useful for several reasons. First, the self-report technique can easily identify preexisting opinion leadership of individuals. Second, self-identification makes it easy to stratify the degree of opinion leadership (Booth & Babchuk, 1972). Lastly, self-identification, despite its possibility of bias, can ensure objectivity when a reliable scale is established by repeated measures by a variety of scholars. This study counts on a verified scale of opinion leadership. The measure of opinion leadership of the present research was adapted from Noelle-Neumann (1985). She defined opinion leadership by using the concept of ‘personality strength,’ which refers to a feature of individuals’ basic social orientation – a reflection of their leadership abilities, their aptitude at shaping others’ opinions, and their perceived impact on social situations. Measured on a scale consisting of ten statements that tap self-perceptions of leadership and social influence, respondents express agreement with each statement. Considering the unique traits of Twitter, this study drew the following six items from the Noelle-Neumann’s scale: (1) I like to have responsibility; (2) I like to take the leadership when people conduct activities as a group; (3) I enjoy convincing others; (4) I serve as a model for others; (5) I am often a step ahead of others; and (6) I often give others advice and suggestions. Responses were coded as 1 (strongly disagree), 2 (disagree), 3 (neither agree nor disagree), 4 (agree), and 5 (strongly agree). The average was taken to create an index, which had a satisfactory Cronbach’s reliability a value assessed at .71 (M = 22.67, SD = 3.27). Twitter use motivations. Motivations were measured according to three categories. The first category, information seeking, was measured by a two-item index: ‘to obtain useful information’ and ‘to check public opinion.’ For each question, the responses were coded as 1 (strongly disagree), 2 (disagree), 3 (neither agree nor disagree), 4 (agree), and 5 (strongly agree). I took the average to create an index (M = 2.56, SD = 1.37). The second category is mobilization, which is also made up of two questions: ‘to form follower group’ and ‘to provide useful information and share them with others’ (M = 2.19, SD = 1.07). The third category is public expression, which is made up of two questions: ‘to express my political views’ and ‘to comment on news items linked on Twitter’ (M = 2.07, SD = 1.11) Twitter use frequency. Twitter use frequency was measured by asking the respondents how often they use Twitter. Responses were coded as 60 (more than two times every day), 30 (once a day), 13.5 (3–4 times a week), 6 (1–2 times a week), 2 (1–3 times a month), and 1 (less than once a month) (M = 20.19, SD = 24.72). Traditional media use. Traditional media use was measured by asking respondents how much they are exposed to national TV news, local TV news, national newspapers, and local newspapers. The responses were coded as 1 (never), 2 (hardly ever), 3 (sometimes), and 4 (regularly) and then summed up to make an index (Cronbach’s a = .82, M = 10.35, SD = 2.80). Online media use. Online media use was measured by asking respondents how much they use Internet portal news and online news sites. The responses were coded as 1 (never), 2 (hardly ever), 3 (sometimes), and 4 (regularly) (M = 7.45, SD = 2.05). Political talk. Political talk was measured by a two-item index. Respondents were asked how often they talk about politics with: (1) family or friends and (2) co-workers or acquaintances. The responses were coded as 1 (never), 2 (hardly ever), 3 (sometimes), and 4 (regularly), and then summed up to create an index (M = 2.76, SD = .77). Political participation. Political participation was assessed by asking respondents if they were involved in the following fourteen political activities during the last six months: ‘wrote a letter or email to the editor of a newspaper or magazine,’ ‘wrote a letter or e-mail to an elected official,’ ‘contributed money to a social group
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or cause,’ ‘contributed money to a political campaign outside your area,’ ‘forwarded a political e-mail to friends,’ ‘signed an online petition,’ ‘signed a paper petition,’ ‘volunteered for a political campaign,’ ‘visited a web site for a political party or candidate you support,’ ‘visited a web site for a political party or candidate you oppose,’ ‘recruited friends to support a cause or campaign,’ ‘worked for a political party or candidate,’ ‘attended a political rally, speech or meeting,’ and ‘displayed a campaign button, sticker or sign’ (Cronbach a = .80). The responses were coded as 1 (Yes) or 0 (No) (M = 3.37, SD = 2.97). Demographic variables. Several control variables were included in the analyses: age, sex, education, income, party identification, and political orientation. For the party identification, participants were asked to indicate the party with which they identified. Three options were given to them: Republican, Democrat, and no affiliation. Political orientation was measured with a scale ranging from 1 (very liberal) to 7 (very conservative), with 4 being moderate.
4. Results Out of the total sample, 40.4% was male and 59.6% was female. The average age was 26.1. In terms of political party identification, 33.3% of the respondents identified themselves as Democrats, while 15.0% identified themselves as Republicans, including 2.7% of the respondents who said they are affiliated with the Tea Party. 24.1% said they are not affiliated with any parties and 27.6% missed this question. Responses for political orientation were distributed as follows: very liberal (8.2%), liberal (22.1%), somewhat liberal (14.6%), moderate (30.8%), somewhat conservative (10.7%), conservative (8.9%), very conservative (4.1%), and no answer (.7%). According to the Pew Research Center for the People & the Press (2012), 32% of Americans identify themselves as Democrats, while 24% of them say themselves as Republicans as of 2011. Independents constitute 37% of the total population. Gallup Politics. (2012) reports a similar result: Democrat (32%), Republican (27%), and Independent (40%) as of 2011. The sample of this study, despite a little underrepresentation of the independent group, resembles the national trend in party identification distribution. The sample of this research reported a mean opinion leadership score of 22.67 (SD = 3.27) with a range of 12–30 out of possible 30. Based on the past studies (e.g., Kotler, Chandler, Brown, & Adam, 1994; Rogers & Cartano, 1962), this study partitioned the samples to correspond as closely as possible to the 16% of the population (1 SD above the mean) identified as opinion leaders. As a result, 80 respondents were classified as opinion leaders and 350 respondents were classified as nonopinion leaders. The relative low proportion of opinion leaders alleviates the concern that a self-
aggrandizing survey respondents tend to present answers that are socially desirable. With regard to RQ1, two independent-samples t tests were conducted. The results show that there is no significant difference in traditional media use between those with strong opinion leadership and those with weak opinion leadership (t(420) = 1.89, p = .06). The results also revealed no significant difference in online media use between perceived opinion leaders and nonleaders (t(409) = 1.29, p = .20). H1a predicted that information seeking motivation of Twitter users would be positively related to strong opinion leadership. The OLS regression result (Table 1) shows that there is a significant association between Twitter opinion leadership and information seeking motivation (B = .05, p < .05). Thus, H1a was supported. H1b predicted that mobilization motivation of Twitter users would be positively related to perceived opinion leadership. As seen in Table 1, there was a significant relationship between the two variables (B = .04, p < .05). H1c was also supported. Twitter opinion leadership was a significant predictor of public expression motivation (B = .04, p < .05). H2 predicted that opinion leadership would positively relate to the frequency of Twitter use. To test this hypothesis, I ran an OLS regression under the condition that demographic variables are controlled. As seen in Table 1, Twitter opinion leadership was significantly associated with Twitter use frequency (B = .89, p < .05), supporting H2. H3 predicted that the three motivations for Twitter use would mediate the influence of opinion leadership on the frequency of Twitter use. In order to test this hypothesis, additional regression analyses were conducted. The following conditions should be met for a variable to function as a mediator (Baron & Kenny, 1986): (a) a significant effect of the independent variable (opinion leadership) on the presumed mediator (information seeking, B = .05, p < .05); (b) a significant effect of the mediator on the dependent variable (Twitter use frequency, B = 9.99, p < .001); (c) adding the mediators reduces a previous significant relation between the independent and dependent variables (from B = .89, p = .02 to B = .29, p = .40). As seen in Figs. 1 and 2, mobilization and public expression motivations were found to mediate the influence of opinion leadership on the frequency of Twitter use. H4 predicted a positive association between Twitter opinion leadership and political talk and political participation. The analyses support the hypothesis. Those with strong opinion leadership on Twitter were more likely to engage in political discussion with others (B = .03, p < .05) and more likely to engage in political activities (B = .13, p < .01). H5a, 5c, and 5c were tested to find out whether three motivations of Twitter use would predict political talk and political participation. Only public expression motivation was found to have a significantly positive relationship with political talk (B = .17,
Table 1 OLS regression investigating whether opinion leadership influences Twitter use frequency.
Age Gender(male = l] Education Income Political orientation (High: conservative] Opinion leadership R2 (%)
Information seeking motivation
Mobilization motivation
Public expression motivation
Twitter use frequency
0.037( 4.126***) 0.016(0.116) 0.051( 0.538) 0.072(1.704) 0.073 ( 1.663) 0.053(2.568*) 10.0***
0.032( 4.556***) 0.018( 0.168) 0.027( 0.373) 0.069(2.109*) 0.017( 0.494) 0.037(2.307*) 10.2***
0.026( 3.499**) 0.055(0.471) 0.057(0.720) 0.055(1.570) 0.105( 2.890**) 0.040(2.305*) 7.8***
0.851 ( 4.840***) 1.265(0.502) l.046(0.601) 2.071(2.707**) 0.729(0.925) 0.889(2.384*) 10.9***
Note: Cell entries are unstandardized OLS regression coefficients. All entries in parentheses are t statistics. * p < .05. ** p < .01. *** p < .001.
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Fig. 1. Mobilization motivation mediates the effect of opinion leadership on Twitter use frequency. Note: The number in the parenthesis is the OLS regression coefficient without adding the mediating variable (mobilization) as a control variable. p < .05, p < .01, p < .001.
Fig. 2. Public expression motivation mediates the effect of opinion leadership on Twitter use frequency. Note: The number in the parenthesis is the OLS regression coefficient without adding the mediating variable (public expression motivation) as a control variable. p < .05, p < .01, p < .001.
p < .01) and political activities (B = .69, p < .01). The other two motivation variables had not significant bearings on political discussion (information seeking: B = .00, p = .95; mobilization, B = .13, p = .06). In addition, information seeking and mobilization motivation was not found to have significant associations with involvement in political activities (B = .15, p = .47, B = .23, p = .38, respectively). 5. Discussion This research examined several hypotheses and one research question regarding the relationship between opinion leadership, media use motivation, Twitter use, and political engagement. Beyond contributing to what we already know about the role of opinion leadership in the traditional media environment, the results point to three main implications for how opinion leadership on Twitter works in political processes and how it is distinguished from the traditional counterpart. First, it should be noted that opinion leadership on Twitter plays a significant role in arousing individuals who have social surveillance motivations and in leading them to actively use Twitter. The results indicate that Twitter opinion leadership successfully predicts public-affairs related motivations of Twitter use – information seeking, mobilization, and public expression. The higher one’s perceived opinion leadership is, the more one is likely to feel motivated to seek information, mobilize people, and express an opinion publicly. In addition, opinion leadership on Twitter was also found to successfully predict how often people use Twitter. That is, those who have strong opinion leadership are more likely to get motivated to depend on Twitter and thus use Twitter more frequently than those with weak opinion leadership. An additional analysis reveals the mechanism in which opinion leadership becomes significantly associated with Twitter use frequency. The association of opinion leadership and Twitter use frequency was mediated by mobilization and public-expression motivations (H3). These findings not only are consistent with what the uses
Table 2 Hierarchical regression investigating whether Twitter opinion leadership and motivations influence political discussion and political participation. Political discussion
Political participation
Demographics Age Gender(male = 1) Education Household income Political orientation (High = conservative) Opinion leadership 2 R (%)
.006(1.052) 017( 214) .116(2.072) 0.25( 1.019) .065( 2.498*)
.054(2.599*) .491(1.588) .078(367) .004( .043) .307( .125**)
.025(2.057*) 6.97
.130(2.826**) 8.58
Media use motivation Information seeking Moblization Public expression Inc. R2 (%) Total R2 (%)
.004 (.065) .129( 1.893) .170(2.878**) 2.62 9.59
1.54( .729) .228( .882) .690(3.080**) 2.75 11.33
Note: Cell entries are unstandardized regression coefficients. All entries in parentheses are t statistics. ⁄⁄⁄ p < .001. * p < .05. ** p < .01.
and gratifications theory posits but also expand the application scope of the theory by documenting how opinion leaders make choices about one of the social media and how the impact of that medium is mediated through opinion leaders’ motivations for using the medium (Katz, Blumler, & Gurevitch, 1974). Second, Twitter opinion leadership successfully predicted individual opinion leaders’ engagement in political discussion and political participation (H4). Considering that social media often serve as an effective tool of political mobilization (Burns & Eltham, 2009; Christensen, 2011; Neumayer & Raffl, 2008), this finding suggests that opinion leaders using Twitter may be playing a crucial role in encouraging individuals to participate in the public and political process. Several prior studies reported that individu-
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als’ self-perceived leadership qualities are directly related to political actions and civic engagement. For instance, Noelle-Neumann (1999) argued that opinion leaders tend to show higher levels of engagement in their communities. Sheufele and Shah (2000) also contended that self-identified opinion leadership can lead to civic participation. This study not only confirms the previous literature, but also overcomes the limitations of previous studies that only dealt with the role of opinion leadership in the political process, by further investigating the relationships between Twitter use and political engagement and between motivations and political engagement. The testing of H5a, H5b, and H5c showed that the motivation variables, except public expression motivation, failed to predict opinion leaders on Twitter engaging in political activities. Additionally, when I add the Twitter use frequency variable to the hierarchical regression model (Table 2) examining how well opinion leadership and motivations predict political discussion and political participation, Twitter use did not make a significant contribution to the model, which means that Twitter use frequency is not meaningfully associated with political engagement. These results suggest that opinion leadership is more important in leading Twitter users to political processes than media use motivations or Twitter use frequency. It would be reasonable to distinguish the role of opinion leadership of Twitter users from the role of their behaviors of using Twitter. That is, the opinion leadership characteristic of individuals needs to be more highlighted in the new media context than in the traditional media context. The last significant implication of this study is that Twitter opinion leadership takes on some different characteristics than traditional opinion leadership. One piece of evidence showing such difference is that Twitter opinion leadership was not associated with media consumption. Opinion leaders on Twitter did not depend more on traditional or online media content than nonleaders. This is maybe because dominant Twitter users are younger and depend less on the media. Twitter often bypasses the traditional intermediation of the mass media (Wu, Hofman, Mason, & Watts, 2011). As I already mentioned in the literature review, Twitter opinion leaders are expected to rely more on their own expertise than on their social positions. Also, they often engage in a multistep process, because messages on Twitter tend to be disseminated via numerous intermediary channels. Therefore, it is quite plausible that Twitter users are good at creating and distributing information that is not covered much in the existing media. Another piece of evidence may be found in the broad network size of Twitter opinion leaders. When an additional independentsamples t test was conducted as to the relationship between opinion leadership of Twitter users and the number of people who follow them on Twitter, I found that participants with strong opinion leadership on the average had more followers than nonopinion leaders (t(260) = 2.48, p < .5). As aforementioned, Twitter is an innovative medium with open and horizontal networks (Honeycutt & Herring, 2009; Lerman & Ghosh, 2010). Presumably, such unique architecture of Twitter helps individuals to get involved in wider networks than before. Even though this study did not directly compare opinion leaders under the environment of traditional media with those who are accustomed to using social media, the result suggests that Twitter opinion leaders might have broader social networks than other types of opinion leaders, thereby exerting more influence on the general public. This study has several limitations. First, it depended on a nonprobability sampling method, which may undermine the generalizability of the findings. The result of this study can mainly be useful in understanding young adults’ social media use, their perceived opinion leadership, and its impact on political engagement. Second, this study only utilized three types of Twitter use motivations. Future studies need to include more types of motivation.
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Lastly, this study has found that opinion leadership tends to increase Twitter users’ engagement in political processes. Following studies may tackle the nuanced mechanism that works between the two variables by considering mediating variables such as political interest, political efficacy, or political trust. Despite some weaknesses, this article sheds a new light on the understanding of the role of opinion leadership in social media context.
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