Linking Facebook User Types With Civic Participation: From a Communication Infrastructure Perspective

Abstract

The rise of social media has coincided with the emergence of an expressive citizenship model that emphasizes the role of expression in networked environments centering on personal interests. Yet relatively little is known about how civic participation might develop from daily, general social media use. Drawing on communication infrastructure theory, this study uses two-wave survey data from Taiwan to investigate which types of Facebook users are more likely to become civic action takers and how. Results show that high public expressers—those who manifest higher levels of public expression (e.g., updating status)—have more integrated connectedness to the civic information sharing network, which in turn facilitates civic participation. This pathway to civic participation is relatively open to users with diverse levels of political interest. Overall, these findings help to explain how general social media users become civic action takers, presenting important implications for addressing inequalities in civic participation.

Keywords

social media Facebook communication infrastructure theory political interest civic participation

As social media allow users to not only gather but also share civic information in a networked environment, scholarship has increasingly identified a need to expand conceptualizations of citizenship (e.g., Bennett, 2008; Cohen & Kahne, 2012). The traditional or informed citizenship model considers media a source of civic matters that allow citizens to make intelligent decisions about policies (e.g., Delli Carpini & Keeter, 1996). In contrast, the emergent or expressive citizenship model posits that networked online spaces built around private interests can encourage users to express themselves and, ultimately, to engage in civic activities when opportunities arise (for a review, see Kligler-Vilenchik, 2017). With an emphasis on expression in these overtly nonpolitical networked spaces, the expressive model suggests that inequalities in civic or political participation might be ameliorated by inadvertently engaging less politically interested social media users in the processes (e.g., Lane & Dal Cin, 2018; Penney, 2014). Given the theoretical importance of general expressive acts in digital media and their potential implications for participatory divides (Kligler-Vilenchik, 2017), it is essential to understand how civic participation might emerge from the everyday, general use of social media.

However, there are two significant gaps in related inquiries. First, most research focuses on the purposes (e.g., social and entertainment) of social media use in isolation or competition (e.g., Kahne & Bowyer, 2018). Relatively little work considers the combined use of various social media features that may closely reflect patterns of general use in daily lives. Second, with the growing attention from a theoretical perspective (Kligler-Vilenchik, 2017), scant empirical work has explored how general social media use may lead to civic participation. To explain such a relationship, communication infrastructure theory (CIT) is a useful, ecological approach that considers the social media network one is embedded, as prior work has emphasized that multiple agents in social media networks, such as social contacts (SC), belonged groups and subscribed individuals or organizations, collectively shape individuals’ behaviors on the platforms (Thorson & Wells, 2016; Wells & Thorson, 2017). CIT suggests that the communication action context (CAC) or the communication environment is a base from which networks of discussing local affairs develop (i.e., storytelling networks), leading to civic outcomes (Ball-Rokeach et al., 2001; Kim & Ball-Rokeach, 2006).

Drawing on CIT, this study aims to identify social media user types based on their combinatory use of different social media features and examine which users are more likely to become civic action takers and how, with a focus on Facebook—the most popular social media platform worldwide. Scholars have considered social media networks conducive to civic resources as online civic infrastructure (Thorson et al., 2018). Echoing this line of work and building on CIT, this study establishes the concept of civic information network that consists of key agents, including SC, Facebook groups (FG), and subscribed individual or organizational fan (IOF) pages to help users gather and share civic information. This study contends that everyday Facebook use that invites public interactions may facilitate stronger connectedness to the network of civic information gathering and sharing. This, in turn, could pave the way for civic participation. We further examine the extent to which such a process is influenced by political interest because political interest has long been theorized as an important factor that may reinforce participatory divides by only engaging the more politically interested individuals in the democratic process (Bimber et al., 2015; Norris, 2001).

Literature Review

Civic Information Networks

CIT represents an ecological lens of understanding the interaction between structures (e.g., society, networks) and individual media use (Ball-Rokeach, 1998; Dimmick, 2003; Dutta-Bergman, 2004). With a focus on place-based community, the central premise of CIT is that neighborhood storytelling—or any communicative action about local communities embedded in daily communication practices—is an important resource for forming a vibrant civic community (Ball-Rokeach et al., 2001; Kim & Ball-Rokeach, 2006). A communication infrastructure is a “storytelling system set in its communication action context” (Ball-Rokeach et al., 2001, p. 396). A storytelling system or network consists of three types of agents: residents, community organizations, and local media. Individuals with integrated connectedness to storytelling networks—where each agent stimulates the other to talk about the local community—are more likely to identify with the community, feel a sense of community belonging, and take civic actions (Ball-Rokeach et al., 2001; Jung & Kim, 2018; Kim et al., 2019; Nah & Yamamoto, 2017). In contrast to prior work that takes an ecological view to understand how different community structures shape technology use (e.g., Shin, 2008; Shin & Kweon, 2011), CIT further examines the process by which individuals become civic actors, suggesting possible ways to reduce participatory divides.

The rise of digital and mobile technologies has highlighted the importance of investigating individuals’ online communication infrastructures, reflecting a shift from place-to-place to person-to-person communication (Rainie & Wellman, 2012). That is, the emergence of digital media allows people to become the center of networks and connect as individuals. They can transcend physical locations to gather and share information from/to a potentially larger and more diverse set of contacts in online than off-line spaces (Rainie & Wellman, 2012). As social media become an important source of news exposure (Fletcher & Nielsen, 2017), scholarship increasingly conceptualizes social media as a communication infrastructure of its own (An & Mendiola-Smith, 2018; Thorson et al., 2018; Wang et al., 2019). In particular, prior work has conceptualized social media users as curators, subject to curatorial decisions made by others, who can both gather and share content from/to various sources on the platforms (Davis, 2017; Thorson & Wells, 2016). Gathering and sharing information on social media indicates modes of acting as informed and expressive citizens, respectively.

Building on this line of work, the present study proposes the concept of civic information networks that are composed of key agents on social media networks, including SC, online groups, and subscribed individual or organizational pages. To construct the civic information networks, we map the three types of storytellers identified in CIT onto social media (i.e., Facebook): (1) SC, (2) online groups (i.e., FG), and (3) and subscribed pages (i.e., IOF pages; Thorson & Wells, 2016; Wells & Thorson, 2017). SC on social media are important resources for gathering and sharing information about public affairs, which can facilitate democratic participation (e.g., Valenzuela et al., 2018). In addition, online groups provide an intimate social sphere that enables cross-cutting political discussion (Kligler-Vilenchik, 2019) and such involvement is positively associated with civic participation (Bouchillon, 2018). In contrast to groups, subscribed pages of individuals (e.g., journalists and politicians) or organizations (e.g., news media and political parties) are a more structured and top-down venue that offers information about public affairs (e.g., Thorson & Wells, 2016). Wells and Thorson (2017) show that exposure to and interaction with content on the subscribed pages are likely to promote democratic engagement.

Furthermore, just as practices of exposure to and expression of civic information are theorized as different pathways to citizenship (Pingree, 2007), this study differentiates between civic information gathering and sharing networks as forms of civic information networks on social media. It assesses the extent to which users are exposed to, and disseminate content about, public affairs to their various social media contacts. Together, this study draws on CIT to identify civic information networks on social media, characterized by gathering and sharing civic information from/to key agents, which may in turn facilitate civic participation.

Facebook User Types and Civic Information Networks

CIT considers CACs or communication environments to be an important component of communication infrastructure that enables or constrains individual abilities to build integrated networks (Ball-Rokeach et al., 2001; Jung & Kim, 2018; Kim & Ball-Rokeach, 2006; Literat & Chen, 2014; Wilkin, 2013). This view suggests that general, daily communication behaviors on Facebook may reflect the CAC in which users are embedded, influencing the development of civic information networks. This, then, highlights the importance of general Facebook communication behaviors.

CIT posits that CACs vary in openness or the degree to which the contexts encourage interactions (Ball-Rokeach et al., 2001; Kim & Ball-Rokeach, 2006; Literat & Chen, 2014; Wilkin, 2013). Similarly, prior work suggests that Facebook communication behaviors can be classified into three forms based on levels of openness: (1) passive use (consumption of information, such as browsing content), (2) active private use (production of information privately, such as exchanging messages with specific others), and (3) active public use (production of information publicly, such as posting status updates to a potentially broad audience; Frison & Eggermont, 2020). Previous research shows that both active private and active public uses are more likely to promote social interaction than passive use (Burke et al., 2010). The kind of support received from each form of active use may differ. Active public use may enhance perceived support from both distant and close relationships, while active private use may encourage users to share more negative and intimate feelings with close contacts and increase their perception of support from these ties (Karapanos et al., 2016). Overall, prior work shows that Facebook users primarily differ on levels of active public use, which may reflect different levels of openness in CACs.

Given the possible difference in active public use, who is more likely to have stronger connectedness to civic information networks on social media? CIT posits that open CACs facilitate interaction (Ball-Rokeach et al., 2001; Kim & Ball-Rokeach, 2006; Literat & Chen, 2014; Wilkin, 2013). This study thus argues that users with more active public use may have more integrated connectedness to civic information networks, suggesting that they gather or share civic information from/with interconnected, diverse agents— SC, groups, and IOF pages. Two broad mechanisms may explain why. First, prior research suggests that distant contacts on social media are an important means through which users who do not actively seek news and politics are incidentally exposed to these messages (Ahmadi & Wohn, 2018). Because people with higher levels of active public use on social media may have larger networks comprised of more weak ties (Burke et al., 2010), these weak ties facilitate information flow (Granovetter, 1973), increasing the chances of incidental exposure to information about public affairs from various sources (Wells & Thorson, 2017). Thus, those with more active public use on social media may be more likely to access civic information from diverse and interrelated sources or have more integrated connectedness to civic information gathering networks.

Hypothesis 1a: Users with higher levels of active public use (Wave 1 [W1]) have more integrated connectedness to civic information gathering networks on Facebook (Wave 2 [W2]).

Second, expressing oneself on social media in order to maintain relationships or pursue entertainment interests helps users learn skills of expression and become part of “latent publics” or networks that can later be activated for civic causes (e.g., Jenkins et al., 2016). This line of work suggests that users with higher levels of active public social media use may be equipped with better skills to express their views about public affairs. This is because, in daily expression, they have to constantly navigate a collapsed social setting where the audience and reception of their expression are highly uncertain (Thorson, 2014). Further, social ties established through daily interactions can pave the way for those with higher levels of active public social media use to engage in an open and intimate discussion about public affairs (Kligler-Vilenchik, 2019). Accordingly, it is expected that users with higher levels of active public use may have more integrated connectedness to civic information sharing networks.

Hypothesis 1b: Users with higher levels of active public use (W1) have more integrated connectedness to civic information sharing networks on Facebook (W2).

Facebook Civic Information Networks and Civic Participation

Prior CIT-related research consistently demonstrates that integrated connectedness to neighborhood storytelling networks enhances civic participation (Ball-Rokeach et al., 2001; Jung & Kim, 2018). Civic participation refers to citizens’ engagement in voluntary civic activities, online and/or off-line, that aims to resolve community problems (e.g., Erhardt & Freitag, 2019; Park & Kaye, 2017; Verba et al., 1995). Beyond the off-line context, increasing research has demonstrated that social media use is positively associated with civic participation (Boulianne, 2019; Kim et al., 2019).

In particular, prior work suggests that social media use spurs civic outcomes through exposure to and expression of civic or political information. From the view of exposure, social media users who gather more information about public affairs from an integrated network may facilitate participation in civic life through social contagion and/or mobilization efforts from various curators in their networks (Bond et al., 2012; Wells & Thorson, 2017). Thus, social media users with more integrated connectedness to civic information gathering networks may be more likely to participate in civic activities.

Hypothesis 2a: Integrated connectedness to civic information gathering networks on Facebook (W2) is positively associated with civic participation (W2).

Further, research on political expression suggests that expressing oneself politically on social media leads to civic or political participation (e.g., Vaccari et al., 2015). Having stronger connections to sharing networks of civic affairs may enhance civic participation, as such expression helps individuals to elaborate or reaffirm their political views (Pingree, 2007), strengthens individual or collective political efficacy (Halpern et al., 2017), and lays an important foundation for civic participation. Therefore, we expect that social media users with more integrated connectedness to civic information sharing networks are more likely to take civic actions.

Hypothesis 2b: Integrated connectedness to civic information sharing networks on Facebook (W2) is positively associated with civic participation (W2).

According to CIT, CACs (communication environments) enable or constraint individuals’ integrated connectedness to storytelling networks, which in turn influences civic outcomes (Ball-Rokeach et al., 2001; Kim & Ball-Rokeach, 2006). Because users with more active public use may have larger networks with more weak ties (Burke et al., 2010) that can facilitate exposure to public affairs (Wells & Thorson, 2017), these users may have more integrated connectedness to civic information gathering networks, which in turn may increase civic engagement. Furthermore, because expression in informal online spaces can cultivate expressive skills (Jenkins et al., 2016) and social relationships for civic and political actions (Kligler-Vilenchik, 2019), those with higher active public use may be equipped with better skills to express themselves and embedded in social networks that are more open to discussion of civic affairs. Consequently, high public expressers may have more integrated connectedness to civic information sharing networks and in turn are more likely to participate in civic activities, compared to those who are lower in public expression. Therefore, in conjunction with the first set of hypotheses regarding the associations between Facebook user types and Facebook civic information networks, the following hypotheses are posed:

Hypothesis 3a: Users with higher levels of active public use (W1) are more likely to participate in civic affairs (W2) indirectly through more integrated connectedness to civic information gathering networks on Facebook (W2).

Hypothesis 3b: Users with higher levels of active public use (W1) are more likely to participate in civic affairs (W2) indirectly through more integrated connectedness to civic information sharing networks on Facebook (W2).

The Moderating Role of Political Interest

The above discussion suggests that users with higher active public use may develop stronger connections to civic information gathering and sharing networks and, in turn, more frequently engage in civic activities. However, the participatory divide literature has long been concerned that social media use may normalize the divide by only engaging more politically interested people in the democratic process, highlighting the theoretical importance of political interest (Bimber et al., 2015; Norris, 2001). Based on this work, this study further interrogates how levels of political interest might moderate the possible progression from general CACs reflected in mixed day-to-day Facebook use to civic information networks on social media, which in turn facilitates civic participation. Because research remains inconclusive on whether social media use widens or narrows gaps in civic outcomes between the more and less politically interested (e.g., Prior, 2007; Xenos et al., 2014), the following research questions are thus posed:

Research Question 1a: Does political interest (W1) moderate the indirect relationship between active public use of Facebook (W1) and civic participation (W2) through integrated connectedness to civic information gathering networks on Facebook (W2)?

Research Question 1b: Does political interest (W1) moderate the indirect relationship between active public use of Facebook (W1) and civic participation (W2) through integrated connectedness to civic information sharing networks on Facebook (W2)?

Method

Sample

To examine the proposed model (see Figure 1), this study used original data from a two-wave online survey in Taiwan. An online survey research company, Trend Research, helped recruit adult Taiwanese respondents who were 20 years old or above via its online panel and online advertisements posted on various forums and social media platforms. Because this study focused on Facebook use, only those who reported using Facebook were included. While the sample was not probabilistic-based, a matching technique was used to ensure the sample was reflective of the Taiwanese population in terms of gender and geographical location. The first wave (W1) of the survey was collected between August 10 and 31, 2017, with 1,050 valid responses. All respondents from W1 were invited to participate in W2, collected between October 18 and 30, 2017. This study analyzed the 406 respondents who completed both waves of the survey.

Figure 1.

The conceptual model of civic information networks. Note: H represents a hypothesis and RQ refers to a research question. (+) and (−) specify a positive and negative relationship, respectively. Indirect indicates an indirect relationship.

Measures

Facebook user types—Levels of active public use

We first assessed general Facebook use by asking how frequently respondents engaged in seven activities on a 5-point scale, ranging from 1 (never) to 5 (always; W1: α = .76): “browsing posts” (M = 4.18, SD = 0.87), “liking others’ posts” (M = 3.60, SD = 0.97), “commenting on others’ posts” (M = 2.63, SD = 0.85), “sharing others’ posts” (M = 2.92, SD = 0.97), “posting” (M = 2.94, SD = 0.96), “checking-in” (M = 2.65, SD = 0.96), and “using private messaging” (M = 3.38, SD = 1.05).

To further confirm levels of active public use of Facebook, we employed Mplus to conduct latent class analysis (LCA), using the general Facebook use items. Compared to cluster analysis based on a distance measure, LCA is a model-based approach that uses maximum likelihood to estimate the underlying probability distributions of parameters, such as the number of latent classes and the probabilities that respondents are members of a given latent class (Vermunt & Magidson, 2002). Because too many ordered categories can lead to classes that are relatively unstable in LCA analysis (Knight & Brinton, 2017), we assigned each of the items from generic Facebook use to three levels: 1 (never to rarely), 2 (sometimes), and 3 (often to always).

This study relied on common measurements in LCA, including the Bayesian information criterion (BIC) and Lo–Mendell–Rubin (LMR) adjusted likelihood-ratio test to determine the best-fitting model (Geiser, 2013). A significant LMR test indicates that the model provides a better fit than the previous model, with one less latent class. A lower BIC shows a better fit. Based on the LMR test and BIC, results suggested that the three-class model best fits the data (see Online Appendix A). Additional analysis was performed to ensure the robustness of the model selection (Knight & Brinton, 2017). For the three classes, the mean (Class 1 = .88, Class 2 = .82, and Class 3 = .90), median (Class 1 = .95, Class 2 = .85, and Class 3 = .97), and proportions of posterior probabilities exceeding the .5 threshold (Class 1 = 99.5%, Class 2 = 99.7%, and Class 3 = 98.4%) were high, indicating that the model did an adequate job of assigning observations to classes.

Table 1 showed the estimated conditional response probabilities for items from generic Facebook use, which helped to interpret and label the identified classes (Geiser, 2013). Because the major difference across the three classes was their level of active public use, we labeled respondents in Classes 1, 2, and 3 as low, moderate, and high public expressers, respectively. Almost 40% of the respondents were low public expressers, followed by moderate (36.9%) and high (23.6%) public expressers (the descriptive statistics of all variables by three user types were shown in Online Appendix B).

Table 1.

Conditional Response Probabilities by Classes.

Facebook Use Items	Class 1: Low Public Expresser	Class 2: Moderate Public Expresser	Class 3: High Public Expresser
Viewing
Never to rarely	0.109	0.003	0.017
Sometimes	0.261	0.210	0.050
Often to always	0.629	0.787	0.932
Liking
Never to rarely	0.343	0.049	0.000
Sometimes	0.415	0.396	0.058
Often to always	0.242	0.556	0.942
Commenting
Never to rarely	0.864	0.488	0.176
Sometimes	0.106	0.501	0.391
Often to always	0.031	0.011	0.432
Sharing
Never to rarely	0.653	0.256	0.059
Sometimes	0.228	0.581	0.241
Often to always	0.119	0.163	0.701
Posting
Never to rarely	0.813	0.175	0.007
Sometimes	0.137	0.725	0.250
Often to always	0.049	0.101	0.743
Checking-in
Never to rarely	0.857	0.417	0.160
Sometimes	0.126	0.488	0.326
Often to always	0.017	0.095	0.514
Messaging
Never to rarely	0.361	0.186	0.130
Sometimes	0.297	0.479	0.251
Often to always	0.342	0.334	0.619
N	415	387	248

Note. N = 1,050. Those highlighted in gray represent the response categories that best describe each class.

Facebook civic information networks variables

Facebook civic information gathering and sharing networks

We adopted the integrated connectedness to storytelling network formula from Kim and Ball-Rokeach (2006), as follows, to calculate integrated connectedness to Facebook civic information gathering (W1: M = 8.09, SD = 2.45; W2: M = 8.44, SD = 2.37) and sharing networks (W1: M = 6.06, SD = 2.69; W2: M = 6.25, SD = 2.68):

\sqrt{SC \times IOF} + \sqrt{SC \times FG} + \sqrt{FG \times IOF} .

Measurements of SC, IOF pages, and FG were explained below.

SC

Following prior work (Davis, 2017; Lai & Tang, 2018), civic information gathering and sharing from/to SC were measured by asking how often respondents received and shared information about government or public affairs through the Facebook newsfeed from/to “family,” “friends,” and “acquaintances” on a 5-point scale (1 = never to 5 = always). The mean values of civic information gathering (W1: α = .65, M = 2.59, SD = 0.76; W2: α = .68, M = 2.68, SD = 0.80) and sharing from/to SC (W1: α = .77, M = 2.26, SD = 0.86; W2: α = .76, M = 2.42, SD = 0.90) were calculated.

IOF pages

Civic information gathering and sharing from/to IOF pages were captured by asking respondents to report how often they received and shared information about government or public affairs through the Facebook newsfeed from/to “IOF pages” on a 5-point scale (1 = never to 5 = always; W1 gathering: M = 3.08, SD = 1.11; W2 gathering: M = 3.28, SD = 1.09; W1 sharing: M = 1.97, SD = 1.09; W2 sharing: M = 1.98, SD = 1.09).

FG

Civic information gathering and sharing from/to FG were measured by asking: “How often do you receive (share) information about government or public affairs through the Facebook newsfeed from (to) Facebook groups” on a 5-point scale (1 = never to 5 = always; W1 gathering: M = 2.62, SD = 1.16; W2 gathering: M = 2.70, SD = 1.15; W1 sharing: M = 1.96, SD = 1.06; W2 sharing: M = 2.01, SD = 1.09) .

Political interest

To assess political interest, respondents were asked “How interested are you in politics” and responded on a 5-point scale, ranging from 1 (not at all) to 5 (very much; W1: M = 2.78, SD = 1.03).

Civic participation

Respondents were asked to report how often in the past 12 months they were engaged in the following four activities: “community improvement work,” “volunteering,” “community gathering,” and “activities related to local groups about public affairs.” Responses were captured on a 5-point scale, ranging from 1 (never) to 5 (always; W1: α = .89, M = 1.73, SD = 0.78; W2: α = .89, M = 1.82, SD = 0.82). A composite measure was formed by averaging these items.

Control variables

In addition to demographics such as age (M = 33.25, SD = 9.97), gender (female = 54%), education (5-point scale, ranging from 1 = junior high school degree or lower to 5 = postgraduate degree; Mdn = college), and income (12-point scale, ranging from 1 = none to 11= NT$77,001 or higher; Mdn = NT$22,001–NT$26,000), several theoretically relevant factors that may relate to the proposed model were assessed and included as controls. First, since research suggests that psychologically empowered individuals who are more self-efficacious and competent are more interested in public affairs and more likely to engage in civic matters (Leung, 2009), self-efficacy and perceived competence were included as controls. On a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree), composite measures of self-efficacy (five items; e.g., “no matter what comes my way, I am usually able to handle it”; W1: α = .76, M = 4.45, SD = 1.40) and perceived competence (four items; e.g., “I enjoy making my own decisions”; W1: α = .76, M = 4.45, SD = 1.40) were formed by averaging the corresponding items.

Next, prior work indicates that political attitudes, such as the strength of partisanship and political efficacy, are important predictors of political expression and discussion (e.g., Barnidge et al., 2018). Accordingly, strength of partisanship (4-point scale, ranging from 0 = independent to 3 = strong partisan, W1: M = 0.83, SD = 1.03) and political efficacy (seven items on a 5-point scale, ranging from 1 = strongly disagree to 5 = strongly agree; e.g., “I consider myself well qualified to participate in politics;” W1: α = .70, M = 2.93, SD = 0.59) were considered as controls in the analyses.

Finally, to account for the possibility that news use may influence civic engagement (e.g., Shah et al., 2001), news use was measured by asking respondents how many days in the past week they used a range of news sources, including television, print newspapers, and online news websites, using an 8-point scale ranging from 0 (0 days) to 7 (7 days). These items were averaged to form a composite measure of news use (W1: α = .76, M = 4.45, SD = 1.40).

Analytic Strategies

To address the proposed hypotheses and research questions, we began by examining the associations between Facebook user types, civic information networks (mediators), and civic participation (outcome) using ordinary least square regressions. Next, we used the SPSS macro PROCESS (Hayes, 2017) to test the indirect effects of Facebook user types on civic participation through forms of civic information networks and examine whether these proposed mediated effects varied based on levels of political interest (moderated mediation). To conduct mediated-related analyses with repeated measures, following Hayes’s (2017) suggestions, this study included W2 values of civic information networks (mediators) and civic participation (outcome), while using W1 values of these measurements as covariates in the related analyses.

Diagnostic tests were performed to detect the presence of autocorrelation and heteroscedasticity. Because the presence of autocorrelation violates the assumption of independence of residuals in regression analysis, the Durbin–Watson statistic was used to detect whether the first-order autocorrelation was present (Durbin & Watson, 1950). The value of the Durbin–Watson statistic ranges from 0 to 4. A value toward 0 indicates strong positive autocorrelation while a value toward 4 shows strong negative autocorrelation. A value near 2 indicates no autocorrelation. For all the regression analyses in the study, the Durbin–Watson statistics ranged from 1.920 to 1.998, showing little evidence of autocorrelation. To detect heteroscedasticity or the violation of the assumption of constant error variance, the SPSS macro Breusch-Pagan and Koenker test was employed (Daryanto, 2020). Results showed that heteroscedasticity was present in the model that predicted civic participation. Following Hayes and Cai’s (2007) suggestions, a heteroscedasticity-consistent standard error estimator (heteroskedasticity-consistent 3 [HC3]) was used to proceed all the analyses.

Results

The first set of hypotheses predicted that users with higher levels of active public use at W1 had more integrated connectedness to civic information gathering at W2 (Hypothesis 1a) and sharing networks at W2 (Hypothesis 1b). Table 2 showed that integrated connectedness to civic information gathering networks (W2) was not statistically different between high and low public expressers (W1; b = .051, p = .863; Model 1A), high and moderate public expressers (W1; b = .428, p =.118; Model 1B), and low and moderate public expressers (W1; b = −.377, p = .135; Model 1A). Regarding civic information sharing networks (W2), as Table 2 showed, high public expressers (W1) were more likely to have more integrated connectedness to civic information sharing networks (W2) than low (b = .690, p < .05; Model 2A) and moderate public expressers (W1; b =.871, p < .01; Model 2B), while low and moderate public expressers (W1) did not differ significantly from each other (b = −.180, p = .517; Model 2A). Thus, Hypothesis 1a was rejected while Hypothesis 1b was partially supported.

Table 2.

Ordinary Least Squares Regression: Predicting Integrated Connectedness to Civic Information Gathering Network (W2), Civic Information Sharing Network (W2), and Civic Participation (W2).

Predictors	Mediators								Outcome Variable
	Integrated Connectedness to Civic Information Gathering Network (W2)				Integrated Connectedness to Civic Information Sharing Network (W2)				Civic Participation (W2)
	Model 1A		Model 1B		Model 2A		Model 2B		Model 3A		Model 3B
	B (SD)	β	B (SD)	β	B (SD)	β	B (SD)	β	B (SD)	β	B (SD)	β
Age (W1)	.013 (.013)	.054			.021 (.016)	.079			.005 (.004)	.061
Female (W1)	.324 (.216)	.068			.108 (.234)	.020			−.043 (.060)	−.027
Education (W1)	−.186 (.125)	−.069			−.215 (.144)	−.070			−008 (.040)	−.009
Income (W1)	.006 (.042)	.007			−.030 (.049)	−.032			.000 (.013)	−.001
Political interest (W1)	.003 (.129)	.001			−.273 (.135)*	−.104			−.002 (.041)	−.002
Political efficacy (W1)	.210 (.230)	.053			.172 (.255)	.038			.100 (.069)	.072
Strength of partisanship (W1)	.042 (.106)	.018			−.158 (.113)	−.061			−.026 (.030)	−.033
Self-efficacy (W1)	.189 (.238)	.050			.269 (.259)	.062			−.042 (.065)	−.032
Perceived competence (W1)	−.029 (.214)	−.008			−.361 (.210)	−.089			.040 (.056)	.032
News use (W1)	.153 (.063)*	.106			.153 (.077)*	.093			.042 (.019)*	.083
Integrated connectedness to civic information gathering network (W1)	.365 (.057)***	.376			.079 (.073)	.072			−.010 (.017)	−.029
Integrated connectedness to civic information sharing network (W1)	.045 (.061)	.051			.358 (.074)***	.354			−.036 (.019)	−.117
Integrated connectedness to civic information gathering network (W2)									.032 (.016)*	.093
Integrated connectedness to civic information sharing network (W2)									.120 (.021)***	.392
Civic participation (W1)	.462 (.157)**	.152			.670 (.187)***	.194			.527 (.052)***	.500
Low public expresser (W1)			.377 (.252)	.159			.180 (.278)	.067			.207 (.069)**	.251
Mod public expresser (W1)	−.377 (.252)	−.159			−.180 (.278)	−.067			−.207 (.069)**	−.251
High public expresser (W1)	.051 (.294)	.021	.428 (.274)	.181	.690 (.351)*	.256	.871 (.308)**	.323	−.119 (.094)	−.144	.088 (.080)	.107
R ²	.322				.383				.583

Note. N = 400. Standardized coefficients are in partially standardized form.

Significance levels: *p < .01. **p < .01. ***p < .001.

The second set of hypotheses proposed that more integrated connectedness to civic information gathering (W2; Hypothesis 2a) and sharing networks (W2; Hypothesis 2b) were positively associated with civic participation (W2). Table 2 Model 3A showed that integrated connectedness to both civic information gathering (W2; b = .032, p < .05) and sharing networks (W2; b = .120, p < .001) were indeed positively related to civic participation (W2), supporting both Hypotheses 2a and 2b.

To formally test the indirect effects of Facebook user types (W1) on civic participation (W2) through civic information gathering (W2; Hypothesis 3a) and sharing networks (W2; Hypothesis 3b), we used the PROCESS Model 4 with 10,000 bootstrap samples (Hayes, 2017). Significant effects are determined by the lower and higher 95% confidence interval (CI) not containing zero. Table 3 revealed that high public expressers were not significantly different from low (point estimate = .002, 95% CI [−.020, .023]) and moderate public expressers (point estimate = .014, 95% CI [−.004, .040]) in terms of civic participation indirectly through civic information gathering networks. Hence, Hypothesis 3a was rejected. However, high public expressers were more likely than low (W1; point estimate = .083, 95% CI [.004, .168]) and moderate public expressers (W1; point estimate = .104, 95% CI [.034, .183]) to participate in civic activities (W2) indirectly through civic information sharing networks (W2), providing partial support for Hypothesis 3b. Notably, when examining the direct relationship between Facebook user types and civic participation, Table 2, Model 3A showed that high public expressers were not significantly different from low (b = −.119, p = .205) and moderate public expressers (b = .088, p = .270) on civic participation. Moderate public expressers, however, were less likely to engage in civic activities than low public expressers (b = −.207, p < .01). The pattern of results suggested that access to civic information sharing networks was an important mechanism that helped high public expressers who may not be particularly active in civic affairs to become civic action takers.

Table 3.

Indirect Effects of Facebook User Types (W1) on Civic Participation (W2) via Integrated Connectedness to Civic Information Gathering Network (W2) and Sharing Network (W2).

Reference Group	Predictor	Mediator	Point Estimate	CI [Lower, Upper]
Moderate expresser (W1)	High expresser (W1)	Integrated connectedness to civic information gathering network (W2)	.014	[−.004, .040]
Low expresser (W1)	High expresser (W1)		.002	[−.020, .023]
Low expresser (W1)	Moderate expresser (W1)		−.012	[−.037, .004]
Moderate expresser (W1)	High expresser (W1)	Integrated connectedness to civic information sharing network (W2)	.104	[.034, .183]
Low expresser (W1)	High expresser (W1)		.083	[.004, .168]
Low expresser (W1)	Moderate expresser (W1)		−.022	[−.090, .043]

Note. N = 400. Path estimates are unstandardized coefficients based on bootstrapping to 10,000 samples with biased corrected 95% confidence interval (CI). Significant indirect relationships are highlighted in gray.

We further tested whether the indirect pathways from Facebook user types (W1) to civic participation (W2) via civic information networks (W2) were moderated by political interest (W1), using PROCESS Model 7 with 10,000 bootstrap samples (Hayes, 2017). As shown in Table 4, none of the indices of moderated mediation had both lower and higher 95% CI below or above 0, suggesting that none of the indirect relationships were significantly different by political interest. These results suggested that political interest plays little role in moderating the indirect relationships.

Table 4.

Conditional Indirect Effects of Facebook User Types (W1) on Civic Participation (W2) via Integrated Connectedness to Civic Information Gathering Network (W2) and Sharing Network (W2).

Mediator	Reference Group	Predictor	Moderator: Political Interest	Point Estimate	CI [Lower, Upper]
Integrated connectedness to civic information gathering network (W2)	Moderate expresser (W1)	High expresser (W1)	Low	.028	[−.003, .071]
			Moderate	.015	[−.004, .042]
			High	.002	[−.026, .030]
		Index of moderated mediation		−.012	[−.039, .006]
	Low expresser (W1)	High expresser (W1)	Low	.013	[−.014, .047]
			Moderate	.003	[−.018, .024]
			High	−.007	[−.037, .017]
		Index of moderated mediation		−.010	[−.032, .006]
	Low expresser (W1)	Moderate expresser (W1)	Low	−.015	[−.051, .008]
			Moderate	−.012	[−.037, .004]
			High	−.009	[−.036, .013]
		Index of moderated mediation		.003	[−.013, .022]
Integrated connectedness to civic information sharing network (W2)	Moderate expresser (W1)	High expresser (W1)	Low	.142	[.036, .264]
			Moderate	.101	[.029, .179]
			High	.061	[−.037, .156]
		Index of moderated mediation		−.039	[−.118, .027]
	Low expresser (W1)	High expresser (W1)	Low	.077	[−.040, .195]
			Moderate	.083	[.004, .170]
			High	.089	[−.009, .194]
		Index of moderated mediation		.006	[−.063, .076]
	Low expresser (W1)	Moderate expresser (W1)	Low	−.065	[−.171, .023]
			Moderate	−.018	[−.084, .046]
			High	.028	[−.048, .121]
		Index of moderated mediation		.045	[−.009, .113]

Note. N = 400. Path estimates are unstandardized coefficients based on bootstrapping to 10,000 samples with biased corrected 95% confidence interval (CI). Conditions for moderator (political interest) are the mean + and −1 standard deviation from the mean, representing the categories of high, low, and moderate political interest, respectively. Significant indirect relationships are highlighted in gray.

Discussion

How does general social media use relate to civic participation? The findings of this study show that users with higher levels of general public expressive acts access stronger civic information sharing resources on social media, which in turn motivates them to engage in civic affairs. Importantly, this process is equally available to the individuals regardless of their levels of political interest. Drawing on CIT, the results provide empirical support for the expressive citizenship model, which suggests that self-expression in a networked environment built around private interests carries civic values (Kligler-Vilenchik, 2017). The results further highlight the mechanism by which general social media users become civic action takers. In doing so, this study contributes several important theoretical insights to the literature on social media and citizenship.

Although CIT conceptualizes CACs (communication environments) and storytelling networks as two major components that are dynamically related to shape civic outcomes, existing empirical work has paid more attention to the latter than the former (e.g., Kim et al., 2019; Nah & Yamamoto, 2017). This study fully leverages CIT by considering both CACs and civic information networks to examine the mechanism through which different types of social media users take civic actions differently. Consistent with prior work in Belgium (Frison & Eggermont, 2020) and the United States (Smith & Anderson, 2018), our typology of Facebook user types based on their combinatory everyday use shows that users primarily differ on levels of active public use (e.g., posting status updates). These users can be categorized into three types: low, moderate, and high public expressers. This typology may reflect the CAC where users are embedded, indicating different possibilities for interacting with different types of contacts (Ball-Rokeach et al., 2001; Kim & Ball-Rokeach, 2006).

When considering the direct relationship between Facebook user types and civic engagement, high and low public expressers are not significantly different on civic participation. In contrast, the analysis of indirect relationships shows that high public expressers are more likely than others to indirectly become civic participants through their more integrated connectedness to civic information sharing networks. The two seemingly conflicting findings are in line with prior work that suggests that social media use spurred by the motives to socialize with friends and family and to pursue interests in hobbies tend to trigger civic and political actions indirectly through a transformative process as opposed to fostering civic engagement directly (Kligler-Vilenchik, 2013). Building on CIT, it is possible that users who engage in higher levels of active public social media use are becoming embedded in a more open context that provides access to more physical (e.g., larger and more diverse networks), psychological (e.g., more comfortable to express; Jenkins et al., 2016), and sociocultural (e.g., norms of expressive engagement; Shehata et al., 2015) resources for discussing civic matters with others, which in turn facilitates civic participation.

In contrast to prior work that often examines the influence of SC, group interaction, or fan pages on participatory outcomes, separately (e.g., Bouchillon, 2018; Heiss et al., 2019; Kahne & Bowyer, 2018), we adopt the ecological view of CIT by considering multilevel agents in civic information networks in order to better capture their collective influence on civic outcomes. As expected, findings show that both integrated connectedness to civic information gathering and sharing networks are directly and positively related to civic participation. However, further analyses reveal that high public expressers are more likely than others to indirectly become civic participants through more integrated connectedness to civic information sharing networks. By contrast, integrated connectedness to civic information gathering networks plays a little mediating role in this process. The findings echo work on interpersonal political talk, suggesting that conversations about public affairs often arise incidentally as a by-product of daily social interactions (Kligler-Vilenchik, 2019; Minozzi et al., 2019). More importantly, resonating with CIT, which highlights connectedness to integrated storytelling networks, our results emphasize the role of integrated connectedness to sharing networks of SC, groups, and fan pages in the process of civic participation. As groups or organizations are more likely than individuals to function as a relationship broker in general publics’ networks over time (Wang et al., 2019), higher integrated connectedness to sharing networks of multilevel actors may carry more stable and greater capacities to turn high public expressers into civic action takers. In this way, the study lends support to the expressive citizenship model, while emphasizing the importance of incorporating multilevel agents involved in civic information sharing networks on social media in understanding how active public use of social media facilitates civic actions.

This study also addresses concerns about the normalization of participatory divides by examining the extent to which the transformation process from general social media users to civic action takers is more likely to occur among the more politically interested individuals. Results show that the indirect associations do not differ significantly by political interest, indicating that high public expressers, with different levels of political interest, are equally likely to take part in civic affairs through their more integrated connectedness to civic information sharing networks. While this finding is consistent with Xenos et al.’s (2014) work that suggests that social media use may help soften divides in civic participation between the more and less politically interested, it presents a paradox. In order to access civic information resources and become civic action takers, users must be willing to engage in publicly expressive acts on Facebook in the first place. In some sense, this result may reinforce the “rich-get-richer” cycle, since the positive feedback loop is only limited to high public expressers. Echoing CIT, the patterns of result highlight the importance of CACs, suggesting civic consequences for divides in daily content production (Hargittai & Walejko, 2008). Overall, the finding suggests the need to consider what users do in their day-to-day social media use, which may be seemingly nonpolitical in the first place to better understand inequality in civic participation.

The findings of the study also present important practical implications. As results show that disparities in daily, general public expression on social media can shape access to civic information sharing networks and subsequent civic engagement, any civic project seeking citizen engagement may adopt social media platforms in their programs and encourage members to post, share, and comment publicly in their everyday use. Meanwhile, social media platforms like Facebook can implement technological interventions to strengthen users’ interaction with SC, groups, and subscribed pages on the platform, which can pave the way for civic participation.

Limitations and Future Directions

Several limitations of the study should be noted, as they also suggest possible directions for future research. First, while this study provides a nuanced look at user types based on use of various Facebook features, this is but one particular way of identifying user types. Because users differ in terms of social (Brandtzæg, 2012) and informational behaviors (Gil de Zúñiga et al., 2017), future work may further examine user types along these lines. Second, this study does not examine the types of content that users read, liked, shared, commented on, posted, or messaged about in their daily lives. Future work can better understand the mechanisms under which general communicative action on social media relates to accessing civic information by identifying the content that users engage in their daily use of social media. Third, while this study extends the work on social media and citizenship to the Taiwanese context, this study does not consider possible differences across social media sites. As the underlying goal of social media venues—serving content that users gather or share previously—is likely to be common across platforms over time, focusing on Facebook allowed us to evaluate the antecedents and consequences of access to civic information networks on the most popular social media platform in Taiwan as well as many other countries. However, future research should further investigate whether these findings are consistent across different platforms. Finally, as with any survey research, we relied on self-reported measures to assess types of users and forms of civic communication networks. In particular, because it is difficult to capture more diverse types of SC based on various foci of activities (e.g., classmates, colleagues, roommates, club members, or neighbors) in a survey, this study considers the basic forms of SC, including family, friends, and acquaintances. Future work could explore more detailed social media activities and contacts to advance theoretical understanding of civic information networks on social media.

Conclusion

Despite the limitations, this study fills an important gap in the existing research on social media by examining how general social media users become civic action takers. Extending CIT to the social media context, this study proposes the concept of civic information network that describes the networks of civic information gathering and sharing from/to interconnected sources on the platform, echoing the informed and expressive citizenship models, respectively. Findings support expressive citizenship models, suggesting that daily general public expression on Facebook can be an indirect entry point to civic participation due to strong connectedness to civic information sharing networks. Further, while the indirect process is equally likely to happen among more and less politically interested users, disparities in daily, general public expression on social media can shape access to civic information sharing networks and subsequent civic engagement. In other words, this study points to the sources of participatory disparity as a result of general social media use. Delving into the processes and the paths from general social media use to civic engagement is an important topic in contemporary society. More research in different cultural contexts is in need to yield more theoretical and empirical insights into the dynamics of digital technology use and the development of civil society.

Supplemental Material

Supplemental Material, sj-pdf-1-ssc-10.1177_0894439321997142 - Linking Facebook User Types With Civic Participation: From a Communication Infrastructure Perspective

Supplemental Material, sj-pdf-1-ssc-10.1177_0894439321997142 for Linking Facebook User Types With Civic Participation: From a Communication Infrastructure Perspective by Rebecca Ping Yu and Chih-Hui Lai in Social Science Computer Review

Footnotes

Data Availability

Replication data can be obtained from the lead author at uping09@gmail.com

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Hakka Affairs Council and the Ministry of Science and Technology of the Republic of China (MOST 108-2410-H-009-045-SS3).

Software Information

Mplus was used to conduct latent class analysis. The SPSS macro PROCESS was used to exam the proposed associations between variables.

Supplemental Material

The supplemental material is available in the online version of the article.

Author Biographies

Rebecca Ping Yu (PhD, University of Michigan) is an assistant professor in the Department of Communication and Technology at National Yang Ming Chiao Tung University. Her research interests include issues of information and communication technology (ICT) access and political and social implications of ICT use.

Chih-Hui Lai (PhD, Rutgers University, 2012) is an associate research fellow in the Research Center for Humanities and Social Sciences (RCHSS), Academia Sinica. Her research investigates how individuals, groups, and organizations use multiple media modalities to communicate and coordinate, particularly in the face of disasters, and how relationships evolve or emerge through these processes.

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