Spatially Bounded Online Social Networks and Social Capital: The Role of Facebook

Transcription

1 Spatially Bounded Online Social Networks and Social Capital: The Role of Facebook Nicole Ellison Charles Steinfield Cliff Lampe Department of Telecommunication, Information Studies, and Media Michigan State University Paper to be presented at the Annual Conference of the International Communication Association (ICA), June 19-23, 2006 in Dresden, Germany

2 Introduction In this paper, we examine the use of an online social networking site by Michigan State University undergraduates and its relationship to social capital formation and maintenance, integration into college life, and psychological well-being. Facebook is an online social network software application used by university students to articulate existing offline social connections as well as forge new ones. The service constitutes a rich site for researchers interested in the affordances of social networks (e.g., social capital and community formation), due to its heavy usage patterns and technological capacities which bridge online and offline connections. Like other social networking sites, such as Friendster, Tribe.net and MySpace, Facebook enables its users to present themselves in an online profile, accumulate friends who can post comments on each other s pages, and view each other s profiles. They can also join virtual groups based on common interests, see what classes they have in common, and, via the profile, learn each others hobbies, interests, musical tastes, and romantic relationship status. At MSU, Facebook groups range from affiliations based on political sensibilities ( Don't Blame Me, I Voted For Kerry ), social inclinations ( I Drink, I Party, and Dammit I'm awesome! ), geography ( I Live In south complex ), shared interests ( Underwater Hockey ), as well as categories that can best be described as quirky ( The Derek Zoolander Center for Kids Who Can't Read Good and Want to Learn to Do Other Stuff Good Too with 6352 members). Facebook was created in February 2004 by Mark Zuckerberg, a student at Harvard University. According to Zuckerberg, The idea for the website was motivated by a social need at Harvard to be able to identify people in other residential houses (Moyle, 2004). Today Facebook has more than 7.5 million registered members at over 2,000 U.S. colleges and is the seventh-most-popular site on the entire Web with respect to total page views (Cassidy, 2006).

3 The site is tightly integrated into the daily media practices of its users: the typical user spends about 20 minutes a day on the site and two-thirds of them log in at least once a day (Cassidy, 2006). Capitalizing upon the success among college students, Facebook launched a high school version of Facebook in early September In 2006, the company introduced communities for commercial organizations such as Microsoft, Amazon and PepsiCo (Barton, 2006); at the time of this writing, over 4000 organizations had created Facebook directories (Smith, 2006). Although student reception to the affordances of Facebook has been enthusiastic, popular press coverage has focused almost exclusively on the negative repercussions of Facebook use. Many of these problems stem from misalignments between users perceptions about the audience for their profile and the actual audience. Students have been reprimanded for including racist or otherwise problematic content in their profiles and postings and for including inappropriate information that might be accessible by future employers. At Northwestern University, for example, Journalism students who joined such Facebook groups as the Alliance for Unethical Journalism and I Was Raped by a Medill Intern aroused the consternation of Medill faculty (Madrid, 2005). Additionally, privacy advocates fear that students may see Facebook as a safe, students only space and include information, such as home addresses, mobile phone numbers, and class schedules, which might encourage stalking or online identity theft (Stutzman, 2006). Although there has been substantial media coverage of Facebook, there has been little academic work exploring the phenomenon, and most of the current thinking is based on anecdotal evidence as opposed to empirical data. It is this context large numbers of highly embedded users, a unique geographically-bound target audience, high visibility, and widespread public concern coupled with few academic studies of the site that motivated our investigation. In contrast with 2

4 other Facebook research, our focus is cases in which the intended audience and the actual audience are aligned, and what positive outcomes are associated with this kind of use. Literature Review Social Networking Software Social networking sites are online spaces that allow individuals to present themselves, articulate their social networks, and establish or maintain connections with others. These sites can be oriented towards work-related contexts (e.g. LinkedIn.com), romantic relationship initiation, or connecting those with shared interests such as music or politics (e.g. MySpace.com). Users may use the sites communication tools to interact with those they know from offline contexts, such as school, or they may use the sites to meet new people. The way in which these sites allow for new connections to be made between individuals has resulted in proposed legislation which would bar libraries and schools to block minors access to social networking sites such as MySpace and Facebook (McCullagh, 2006). MySpace in particular has generated public concern due to its large member base million registered accounts according to one source (Wright, 2006) many of whom are teenagers. There is little academic work examining online social networks. A 2005 survey of academic community members found that 90% of the undergraduates participated in a social network community, primarily Facebook, MySpace, and Friendster, and that many of them disclosed personal information such as address (Stutzman, 2006). In her ethnographic work examining self-presentation and social connections among Friendster users, boyd (2004) notes that users have a variety of motivations for using the site, including connecting with old friends, meeting new acquaintances, dating, and furthering professional networks. In one of the few pieces to examine this new breed of online fora, Donath and boyd (2004) point out that one 3

5 of the chief hallmarks of these sites is that links between individuals are mutual, public, unnuanced and decontextualized. In the sites that Donath and boyd examine, public displays of connections serve to warrant, or signal the reliability of, one s identity claims. Social networking sites are distinguished from the first wave of virtual community sites in that they allow for both maintenance of existing social ties and formation of new connections. A hallmark of the early research on computer-mediated communication and virtual communities in particular is the assumption that individuals using these systems would be connecting with those outside their pre-existing social group or location, liberating individuals to form communities around shared interests, as opposed to shared geography (Wellman et al., 1996). However, some online community researchers have explored how online communities present opportunities for people in a common offline community to extend their interaction. Such a theme is articulated by Wellman et al. (1996), who note that Although CSSNs [computersupported social networks] do transcend time and space, not all ties are either totally on-line or off-line. Much on-line contact is between people who see each other in person and live locally (p.222). Nonetheless, when online and offline social networks overlapped, the direction was typically online to offline online connections that resulted in face-to-face meetings. For instance, Rheingold (2000) discusses members of the online WELL community getting together for picnics, and Parks and Floyd (1996) report that one-third of their respondents had met their online correspondents face-to-face. As they write, These findings imply that relationships that begin on line rarely stay there. So, although early work acknowledged the ways in which offline and online networks bleed into one another, many early virtual communities explicitly connected people based on shared interests as opposed to shared geography and facilitated meetings 4

6 between individuals with no previous offline connection. Today s online social networking sites are different in that they are structured to both facilitate meetings with new individuals as well as maintain existing ties. However, there have been no empirical studies to date that measure the extent to which members use these online social networking sites to maintain existing ties or to form new ones. This issue is certainly true for geographically-based social networking sites such as Facebook, which may exemplify an understudied offline to online trend. Facebook distinguishes itself from other online social networks in that it primarily serves a geographically bound community (the campus) and by the fact that, at least for the college and university version of Facebook, membership is restricted to those with a specific host institution address. In this sense, it is similar to the wired Toronto neighborhood studied by Keith Hampton and Barry Wellman (e.g. Hampton, 2002; Hampton & Wellman, 2003). Their work supports the view that information technology may enhance place-based community and facilitate the generation of social capital. As in the Netville community studied by Hampton and Wellman, Facebook members share more offline connections and are more likely to anticipate meeting one another in offline spaces. In other contexts, anticipated face-to-face interaction has been shown to increase the honesty of self-presentational messages (Gibbs et al., 2006). Facebook may therefore necessitate a different set of research questions due to the fact that participants will be less likely to play with their identities (and therefore to verify others ) due to the geographically bound nature of the site. The existing academic research on Facebook has focused on identity presentation and privacy concerns (Gross & Acquisti, 2005; Stutzman, 2006) or analysis of the network structure (Hamatake et al., 2005). Looking at the amount of information Facebook participants provide 5

7 about themselves, the relatively open nature of the information, and the lack of privacy controls enacted by the users, Gross and Acquisti (2005) argue that users may be putting themselves at risk for attacks on both offline (such as stalking) and online (such as identify theft). While the apparent schism between Facebook users imagined audience and the actual audience, in conjunction with the highly public nature of the presentation, are cause for concern, we believe an equally important research question concerns the question of whether Facebook users are able to capitalize on the networking capacities of Facebook. Donath and boyd (2004) hypothesize that online social networking sites may not increase the number of strong ties a person may have, but could greatly increase the weak ties one could form and maintain because the technology is wellsuited to maintaining these ties cheaply and easily. As they write, If this is true, it implies that the technologies that expand one s social network will primarily result is an increase in available information and opportunities the benefits of a large, heterogeneous network (Donath & boyd, 2004, p. 80). However, this argument has yet to be tested. We adopt the social capital lens as a way to determine whether these sites are actually associated with increases in useful connections, information and opportunities. Social Capital: Online and Offline In this paper, we are interested in the effects of social networking systems like Facebook on the production of social capital, the resources accumulated through the relationships among people (Coleman, 1988). The social capital concept is an elastic term with a variety of definitions in multiple fields (Adler & Kwon, 2002), conceived of as both a cause and an effect (Williams, 2006). Bourdieu and Wacquant (1992) define social capital as the sum of the resources, actual or virtual, that accrue to an individual or a group by virtue of possessing a durable network of more or less institutionalized relationships of mutual acquaintance and recognition (p. 14). The 6

8 resources from these relationships can differ in form and function based on the relationships themselves. An alternative definition is provided by Huysman and Wulf (2004), who write, Social capital refers to network ties of goodwill, mutual support, shared language, shared norms, social trust, and a sense of mutual obligation that people can derive value from. It is understood as the glue that holds together social aggregates such as networks of personal relationships, communities, regions, or even whole nations (p. 1). Social capital has been linked to a variety of social outcomes such as better public health, lower crime rates, and more efficient financial markets (Adler & Kwon, 2002). According to several measures of social capital, this important resource has been declining in the United States for the past several years (Putnam, 2000). When social capital declines, a community experiences increased social disorder, reduced participation in civic activities, and potentially more distrust between community members. Increased social capital increases commitment to a community, and ability to mobilize collective actions, among other benefits. Social capital may also be used for negative purposes, but in general social capital is seen as a positive effect of interaction between participants in a social network (Helliwell & Putnam, 2004). For individuals, social capital allows individuals to benefit in a variety of ways in that participation in a social network allows a person to draw on resources from other members of the network and to leverage connections from multiple social contexts. These resources can take the form of important information, employment opportunities, personal relationships, or the capacity to organize groups (Paxton, 1999). Access to individuals outside one s close circle provides access to non-redundant information, resulting in benefits such as employment connections (Granovetter, 1973). 7

9 These loose connections are often referred to as weak ties (Granovetter, 1982). Within social networks, the existence of gaps i.e. the absence of direct links among all participants - between connected individuals can actually increase the efficiency of information flows within the larger network. Members of the social network who act as hubs tie together sub-networks and act as brokering agents. Burt (2000) refers to these gaps in social networks as structural holes and argues that networks operate more efficiently when structural holes exist, often by supporting the importing and exporting of new information and ideas between sub-groups. Such a process allows information to flow from one group in which it is common knowledge or mundane, to another where it is new and may be more valuable. Putnam (2000) distinguishes between bridging and bonding social capital. These weak ties are closely linked to bridging social capital, which is inclusive and refers to loose connections between individuals who may provide useful information or new perspective for one another, but typically not emotional support. Alternatively, bonding social capital is found between individuals in tightly-knit, emotionally close relationships, such as family and close friends. We briefly highlight these two forms of social capital below, as well as a third form high school social capital - that we felt might address a particular need of college students moving from home to their university locale. Bridging Social Capital and the Internet. Putnam concludes that one of the main causes of the decrease in social capital is the long-term decrease in participation in voluntary associations like the Elks club or bowling leagues. Some researchers have claimed that online interactions may supplement or replace those interactions that previously were formed in voluntary organizations (Wellman et al., 2001). Since online relationships may be supported by technologies like recommender systems, distributions lists, photo directories and search 8

10 capabilities (Resnick, 2001), it is possible that new forms of social capital and relationship building might occur in online sites like Facebook. This kind of participation is closely linked to bridging social capital and might be augmented by the sites like Facebook, which support loose social ties, allowing users to create and maintain larger, diffuse networks of relationships from which they could potentially draw resources (Donath & boyd, 2004; Resnick (2001); Wellman et al., 2001). Indeed, studies of physical (i.e. geographical) communities supported by online networks, such as the Netville community in Toronto or the Blacksburg Electronic Village, have concluded that computer-mediated interactions have had positive effects on community interaction, involvement and social capital (Hampton & Wellman, 2003; Kavanaugh & Patterson, 2001; Kavanaugh et al., 2005). Bonding social capital and the Internet. In Putnam's (2000) view, bonding social capital reflects strong ties with family and close friends, who might be in a position to provide emotional support or access to scarce resources. Williams (2006) points out that little empirical work has explicitly examined the role of the Internet on bonding social capital, although some studies have questioned whether the Internet supplements or supplants such strong ties. Quan- Haase and Wellman (2004) review the literature on the Internet s impact on social capital and categorize the extant literature into three main arguments: the Internet transforms social capital (by providing individuals with the means by which to find others with similar interests, to the detriment of established offline communities); the Internet diminishes social capital (by attracting people away from existing offline social networks); and the Internet supplements social capital (by blending into and supporting existing social relations as well as facilitating new ones). It is evident that the Internet facilitates new connections: the Internet provides people with an alternative way to connect with individuals that share their interests (Horrigan, 2002; Parks & 9

11 Floyd, 1996) or to identify new romantic partners (Ellison et al., 2006). These new connections may result in an increase in social capital; for instance, a 2006 Pew Internet survey reports that online users are more likely to have a larger network of close ties than non-internet users and that Internet users are more likely than non-users to receive help from core network members (Boase et al., 2001). However, it is unclear how social capital formation occurs in a context in which online and offline connections are closely coupled, as with Facebook. Williams (2006) argues that although researchers have examined potential losses of social capital in offline communities due to increased Internet use, they have not adequately explored online gains that might compensate for this. High School Social Capital. Social networks change over time as relationships are formed or abandoned. Particularly significant changes in social networks may occur when a person moves from the geographic location in which their network was formed. Putnam (2000) argues that one of the possible causes of decreased social capital in the United States is the increase in families moving for job reasons. Facebook s target audience is college students, a group that can be considered to be in a state of transition regarding social networks. We therefore thought it would be useful to introduce a form of bridging social capital focusing on connections from high school. Young adults moving to college leave friends from high school with whom they may have established rich networks, and need to reformulate networks in their new locale. In terms of benefits that may be accrued from social networks, completely abandoning the network from high school would also be a loss of potential social capital. Granovetter (1973, 1982) has suggested that weak ties provide more benefit when the weak tie is unassociated with stronger ties, as may be the case for maintained high school relationships. To test the role of maintained high school relationships as weak, bridging ties, we adapted questions 10

12 about general bridging relationships, such as those in Williams (2006), to be specific to maintained relationships with high school acquaintances. Based on this brief review of the online social network and social capital literature, our empirical analysis of one Facebook community is guided by three broad research questions: RQ1: Who is using Facebook? Are there differences, such as by gender, year in school, or residential status, between those who join and those who do not that might shed light on its role in facilitating or hindering students' abilities to form and maintain social capital? Moreover, are there differences on other psychological measures such as self esteem or satisfaction with life between Facebook members and non-members? RQ2: How are students using Facebook? Is there a difference in students' use of profile elements, their motivations for using Facebook, or the extent to which they use it that can shed light on its role in facilitating or hindering students' abilities to form and maintain social capital? RQ3: What is the relationship between Facebook use and social capital? Does greater use imply increase or decrease students' abilities to form and maintain various types of social capital? Do different motivations for use, such as using Facebook explicitly to keep in touch with old friends, or using it to explicitly to seek out new information and/or people, yield different outcomes vis-a-vis social capital formation? Method A random sample of 800 Michigan State University undergraduate students was retrieved from the MSU Registrar s office. All 800 students were sent an invitation from one of the authors, with a short description of the study, information about confidentiality and an incentive for participation, and a link to the survey. Participants were compensated with a $5 credit to their SpartanCash accounts, used to purchase food, books, or other items. The survey was hosted on 11

13 Zoomerang ( a commercial online survey hosting site, and was fielded in April, We focused on undergraduate users and did not include faculty, staff, or graduate students in our sampling frame. Two reminder s were sent to those who had not responded. A total of 286 students completed the online survey, yielding a response rate of 35.8% (see Table 1 for sample demographics). Table 1. Sample Demographics (N=286) Mean or % (N) S.D. Gender: male female 34% (98) 66% (188) Age Ethnicity white non-white 87% (247) 13% (36) Income Year in school Home residence: in-state out-of-state 91% (259) 09% (25) Local residence: on campus off campus 55% (157) 45% (127) Member of fraternity or sorority 08% (23) 1.01 Hours of Internet use per day 2 2 hours 56 min. 1:52 Facebook members 94% (268) 1 1=under $20,000, 2=$20,000-$34,999, 3=$35,000-$49,999, 4=$50,000-$74,999, 5=$75,000 or more 2 1=first year, 2=sophomore, 3=junior, 4=senior 3 converted from ordinal scale using mid-point of response category (e.g. 1-2 hours = 1 hour 30 minutes) Measures Our instrument included four broad types of measures, briefly described below: demographic and other descriptive variables such as gender, age, year in school, local vs. home residence, ethnicity, a measure of Internet use adapted from LaRose et al. (2005), and whether respondents were Facebook members or not. These items are reflected in Table 1 above. 12

14 Facebook usage measures, including items covering time spent using Facebook, usage of various Facebook features, and purposes for using Facebook. We further included a set of items that measured users' perceptions that the people with whom they communicate are also Facebook users. Psychological measures, including items measuring self-esteem as well as students' satisfaction with their life at the university. Social capital measures, which served as our dependent variables. We adapted several existing measures to reflect aspects of social capital we felt were most salient for this population, as suggested by Quan-Haase & Wellman (2004): The Internet leads to new forms of social capital that cannot be easily captured with existing forms of measurement. Thus, to assess the full impact of the Internet on social capital, researchers need to develop new forms of measurement that complement existing ones (p. 124). Measures of Facebook Usage Facebook Intensity. As shown in Table 2, this scale gives us a more nuanced measure of how Facebook is being used than would simple items assessing frequency or duration of use. This measure includes two self-reported assessments of Facebook behavior: the number of Facebook friends and the amount of time spent on Facebook on a typical day. These items were designed to measure the extent to which the participant was actively engaged in Facebook behaviors. This measure also includes a series of attitudinal questions designed to tap into the extent to which the participant was emotionally connected to Facebook and the extent to which Facebook was integrated into one s daily activities. Using a 5-point Likert scale, participants rated the extent to which they agreed or disagreed with the following statements: Facebook is part of my everyday activity; I am proud to tell people I m on Facebook; Facebook has become 13

15 part of my daily routine; I feel out of touch when I haven t logged onto Facebook for a while; I feel I am part of the Facebook community; I would be sorry if Facebook shut down. These two sets of items were standardized due to their different scale ranges, and then averaged to create a Facebook Intensity scale (Cronbach's alpha=.83). Table 2. Summary Statistics for Facebook Intensity Individual Items and Scale Mean S.D. Facebook Intensity 1 (Cronbach's alpha=0.83) About how many total Facebook friends do you have at MSU or elsewhere? 0=10 or less, 1=11-50, 2=51-100, 3= , 4= , 5= , 6= , 7= , 8=more than In the past week, on average, approximately how many minutes per day have you spent on Facebook? 0= less than 10, 1=10-30, 2=31-60, 3=1-2 hours, 4=2-3 hours, 5=more than 3 hours Facebook is part of my everyday activity I am proud to tell people I'm on Facebook Facebook has become part of my daily routine I feel out of touch when I haven't logged onto Facebook for a while I feel I am part of the Facebook community I would be sorry if Facebook shut down Individual items were first standardized before taking an average to create scale due to differing item scale ranges. 2 Unless provided, response categories ranged from 1=strongly disagree to 5=strongly agree. Types of Facebook Uses. We explored how students used Facebook with several 5-point Likert scale items that tapped two potential functions of Internet use: primarily information seeking (Cronbach's alpha=.75) vs. more entertainment-oriented uses (Cronbach's alpha=.77). Additionally, to investigate whether usage was more motivated by prior offline contacts or the potential to form new online ones, we developed several items reflecting each. Both sets of items are described in Table 3. In the former case, the items measured whether respondents used Facebook to look up someone with whom they shared some offline connection (such as someone they were friends with or with whom they shared a class or living area) (Cronbach's alpha=.70). In the latter case, our instrument included several items that tapped the use of Facebook mainly to make new friends without any reference to offline connection, but these did not correlate 14

16 highly, and our final analysis incorporated only a single item measure: using Facebook to meet new people. Perceived Critical Mass. Another measure that tapped the extent to which Facebook usage was influenced by prior connections is whether respondents felt that their contacts were also using Facebook (Table 3). We called this scale perceived critical mass, which was adapted from the scale used by Ilie et al. (2005) in their diffusion of innovation study. The answers to these questions were reported on a 5-point Likert scale. We also added two original items to the scale, which resulted in a scale reliability of Cronbach s alpha =.80. Table 3. Summary Statistics for Motivations for Using Facebook Individual Items and Scales 1 Mean S.D. Use Facebook for filling up free time, taking breaks, fun (Cronbach's alpha=0.77) I use Facebook to fill up free time I use Facebook to take a break from doing my homework I browse Facebook just for fun Use Facebook to find out about events, trends, music, or get information (Cronbach's alpha=0.75) I use Facebook to find out about things going on at MSU I use Facebook to keep up to date on current trends I use Facebook to find out about new music or movies I use Facebook to get useful information Off to Online: Use Facebook to connect with offline contacts (Cronbach's alpha=0.70) I have used Facebook to check out someone I met socially I use Facebook to learn more about other people in my classes I use Facebook to learn more about other people living near me I use Facebook to keep in touch with my old friends On to Offline: I use Facebook to meet new people (single item measure) Critical mass of friends on Facebook (Cronbach's alpha=0.86) Many people I communicate with use Facebook The people I communicate with will continue to use Facebook in the future Of the people I communicate with regularly, many use Facebook Individual items ranged from 1 = strongly disagree to 5 = strongly agree, scales constructed by taking mean of items. 15

17 Psychological Measures Satisfaction with Life at MSU. The scale of satisfaction with life at MSU was adapted from the Satisfaction with Life Scale (SWLS) (Diener et al., 1997; Pavot & Diener, 1993). The scale is a short 5-item instrument designed to measure global cognitive judgments of one s lives. The answers to these questions were reported on a 5-point Likert scale. The reliability test for the scale showed a relatively high reliability with Cronbach s alpha =.87 (Table 4). Table 4. Summary Statistics and Factor Analysis Results for Self Esteem and Satisfaction with MSU Life Items Individual Items and Scales 2 Mean S.D. Self Esteem Factor Loadings 1 Satisfaction with MSU Life Self Esteem Scale (Cronbach's alpha=0.87) I feel that I'm a person of worth, at least on an equal plane with others I feel that I have a number of good qualities All in all, I am inclined to feel that I am a failure (reversed) I am able to do things as well as most other people I feel I do not have much to be proud of (reversed) I take a positive attitude toward myself On the whole, I am satisfied with myself Satisfaction with MSU Life Scale (Cronbach's alpha=0.87) In most ways my life at MSU is close to my ideal The conditions of my life at MSU are excellent I am satisfied with my life at MSU So far I have gotten the important things I want at MSU If I could live my time at MSU over, I would change almost nothing Principal components factor analysis with varimax, explaining 62% of the variance. 2 Individual items ranged from 1 = strongly disagree to 5 = strongly agree, scales constructed by taking mean of items. 16

18 Self-Esteem. Self-esteem was measured by adopting the Rosenberg Self-Esteem Scale (Rosenberg, 1989). It is one of the most widely-used self-esteem measures in social science research. The answers to these questions were reported on a 5-point Likert scale. Our measures resulted in a scale reliability of Cronbach s alpha =.87 (Table 4). Measures of Social Capital Our three measures of social capital bridging, bridging, bonding, and high school social capital were adapted from scales used in prior studies, with several new items added, and wording changed to reflect the context of the study. The full set of social capital items were factor analyzed to ensure that they did reflect three distinct dimensions (see Table 5). Bridging Social Capital. This measure was intended to asses the extent to which participants experienced bridging social capital. According to Williams (2006), Putnam suggested that the social capital derived from bridging, weak-tie networks is "better for linkage to external assets and for information diffusion" (2000, p. 22) Also, members of weak-tie networks are thought to be outward looking and to include people from a broad range of backgrounds. The social capital created by these networks generates broader identities and generalized reciprocity. Putnam implied some criteria that were the starting points for theorizing: 1) outward looking; 2) contact with a broader range of people; 3) a view of oneself as part of a broader group; and 4) diffuse reciprocity with a broader community. We therefore adapted five of Williams (2006) Bridging Social Capital subscale and created three additional items intended to prove these dimensions of bridging social capital in the MSU context. One item, MSU is a good place to be was included because it loaded on the same factor and tapped into an outcome of bridging social capital (Cronbach's alpha=.87). 17

19 Table 5. Summary Statistics and Factor Analysis Results for Social Capital Items Individual Items and Scales 2 Mean S.D. Bridging Social Capital Scale (Cronbach's alpha=0.87) Bridging Social Capital Factor Loadings 1 Bonding High School Social Social Capital Capital I feel I am part of the MSU community I am interested in what goes on at MSU MSU is a good place to be I would be willing to contribute money to MSU after graduation Interacting with people at MSU makes me want to try new things Interacting with people at MSU makes me feel like a part of a larger community I am willing to spend time to support general MSU activities At MSU, I come into contact with new people all the time Interacting with people at MSU reminds me that everyone in the world is connected Bonding Social Capital Scale (Cronbach's alpha=0.75) There are several people at MSU I trust to solve my problems If I needed an emergency loan of $100, I know someone at MSU I can turn to There is someone at MSU I can turn to for advice about making very important decisions The people I interact with at MSU would be good job references for me I do not know people at MSU well enough to get them to do anything important (reversed) High School Social Capital Scale (Cronbach's alpha=0.81) I'd be able to find out about events in another town from a high school acquaintance living there If I needed to, I could ask a high school acquaintance to do a small favor for me I'd be able to stay with a high school acquaintance if traveling to a different city I would be able to find information about a job or internship from a high school acquaintance It would be easy to find people to invite to my high school reunion Principal components factor analysis with varimax rotation, explaining 53% of the variance. 2 Individual items ranged from 1 = strongly disagree to 5 = strongly agree, scales constructed by taking mean of items. 18

20 Bonding Social Capital. Bonding was assessed using a subset of the Internet Social Capital Scales developed and validated by Williams (2006). Responses were reported on a 5-point Likert scale. Five items were adapted to the MSU context (Cronbach s alpha =.75.) High School Social Capital. This original scale was inspired by our pilot interviews, media coverage of Facebook, and anecdotal evidence that suggested keeping in touch with high school friends was a primary use of Facebook. These items were adapted from traditional measures of social capital which assess an individual s ability to mobilize support or action (Cronbach's alpha=.81). Findings Our first research question asked who is using Facebook. Given the incredibly strong penetration of Facebook on college campuses, the short answer is just about all students. In our sample, 94% of the students keeping in mind that we only surveyed undergraduates were Facebook members. We investigated whether members and non-members differed significantly along various demographic characteristics, and as shown in Table 6, there were few differences. Neither gender, ethnicity, nor income appeared to relate to propensity to join Facebook. Older students, and those who have been at school longer are significantly less likely to be on Facebook, probably reflecting an effect of the recency which with the MSU Facebook community began. There are slight indications that on-campus students might be more likely to join than off-campus students, however this is likely related to age, as MSU requires first year students to live on campus. Moreover, due to the small number of non-members, this effect is not significant. Out-of-state students are also slightly less likely to be on Facebook, although this again is not significant. Interestingly, all of the 23 fraternity and sorority members in our sample were Facebook members, suggesting that peer influences might play a role. It is also 19

21 worth noting that GPA did not differ between members and non-members, and non-members used the Internet as often as members. There are some tendencies for Facebook members to report higher satisfaction with MSU life, bridging and bonding social capital, but these were not significant due to the small number of non-members. However, members report significantly higher high school social capital. Table 6. Comparisons Between Facebook Members and Non-Members on Independent and Dependent Variables Members (N=268) Non-Members (N=18) Sig. of Difference T-test or Chi- Independent Variables Mean or % S.D. Mean or % S.D. Square 1 P 2 Gender: male (n=98) 92.86% 7.14% female (n=188) 94.15% 5.85% 0.18 Ethnicity: white (n=247) 93.93% 6.07% non-white (n=36) 91.67% 8.33% 0.25 Age ** Income Year in school ** GPA Home residence: in-state (n=259) 94.21% 5.79% out-of-state (n=25) 88.00% 12.00% 1.22 Local residence: on campus (n=157) 95.54% 4.46% off campus (n=127) 91.34% 8.66% 2.08 Fraternity/sorority member (n=23) nonmember (n=263) % 93.16% 0.00% 6.84% 3.12 Hours of Internet use per day 2:56 1:49 2:58 2: Self esteem Satisfaction with life at MSU Bridging social capital Bonding social capital High school social capital ** 1 Chi-Square likelihood ratios for nominal variables and two-tailed T-test scores assuming equal variances for continuous variables 2 *=P<.05, **=P<.01, ***=P<.001, ****=P<.0001 Our second research question asked how students were using Facebook. As shown in Table 2, students report spending between 10 and 30 minutes on average using Facebook each day and report having between 150 and 200 friends on the system. They are significantly more likely to use Facebook for fun and killing time (mean=3.60) than for gathering information (mean =2.25)(t=22.62, p<.0001). They also report significantly more Facebook use involving 20

22 people with whom there is some offline connection - either an existing friend, a classmate, someone living near them, or someone they met at a party (mean=3.64) - than for meeting new people (mean=1.97) (t=26.14, p<.0001). Respondents were very likely to agree that their friends are also using Facebook and would continue to do so (mean=4.07). Further insight in Facebook usage patterns can be gleaned from Figures 1 and 2, which show what elements respondents report including in their Facebook profile and who they believe has seen their profiles, respectively. The fact that nearly all Facebook users include their high school name in their profile (96%) suggests that maintaining connections to former high school classmates is a strong motivation for using Facebook. Not surprisingly, 97% report that high school friends had seen their profile. Ninety percent or more also reported that other friends as well as people in their classes had seen their profile, further suggesting an offline component to Facebook use. Figure 1. Elements in Respondents' Facebook Profiles 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% My high school My relationship status A photo of just me My AIM screen name My classes A photo with me and others My mobile number 21

23 Figure 2. Who Has Viewed Respondents' Facebook Profiles 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% People in my classes My high school friends Other friends Total stranger at MSU Someone I met at a party Family My resident mentor Total stranger another campus Total strangers not at a school My professors Administration Law enforcement In order to explore RQ3 - how Facebook use related to the various forms of social capital reported by students, we conducted three different regression analyses (see Table 7). First, in model 1, we investigated the extent to which demographic factors, self esteem and the adapted satisfaction with life scales, Internet use, and Facebook intensity predicted the amount of bridging social capital reported by students. We also explored whether Facebook use interacted with self esteem and satisfaction with MSU life. Overall, these factors explained nearly half of the variance in bridging social capital. The results suggest that Facebook is having a large impact on students' ability to develop and maintain bridging social capital at college. White students are somewhat more likely to have bridging social capital than non-white students 22

24 (scaled beta=.08, p<.05)), as are students satisfied with life at MSU (scaled beta=.66, p<.0001). Those who use Facebook more intensely report higher bridging capital (scaled beta=.34, p<.0001). It is important to note that general Internet use was not a significant predictor of bridging social capital. Facebook use interacted with the psychological measures, as shown in Figures 3 and 4. Those reporting low satisfaction and low self esteem appeared to gain in bridging social capital if they used Facebook more intensely, suggesting that the online social network might be especially helpful for these respondents. Table 7. Regressions Predicting Amount of Social Capital from Demographic, Attitudinal, and Facebook Variables Model 1: Bridging Social Capital Scaled Model 2: Bonding Social Capital Model 3: High School Social Capital Scaled Beta Beta 2 P 3 Independent Variables 1 Beta P P Scaled Intercept 3.80 **** 3.73 **** 3.57 **** Gender: male Gender: female] Ethnicity: white 0.08 * 0.17 ** 0.23 *** Ethnicity: nonwhite * ** *** Income Year in school *** State residence: in-state State residence: out-of-state Local residence: on campus ** Local residence: off campus ** 0.06 Fraternity/sorority member Not member of fraternity/sorority Hours of Internet use per day * Self esteem ** 0.30 *** Satisfaction with life at MSU 0.66 **** 0.40 *** Facebook (FB) intensity 0.34 **** 0.37 **** 0.37 *** Self esteem by FB intensity ** Satisfaction by FB intensity *** with self esteem by FB intensity with satisfaction by FB intensity N=269 F=18.83 **** Adj R 2 =.44 F=19.92 **** Adj R 2 =.46 N=269 F=7.60 **** Adj R 2 =.23 F=7.48 **** Adj R 2 =.22 N=269 F=5.88 **** Adj R 2 =.17 F=5.40 **** Adj R 2 =.16 1 Nominal factors expanded to all levels 2 Continuous factors centered by mean, scaled by range/2 3 *=P<.05, **=P<.01, ***=P<.001, ****=P< Only one interaction term was entered at a time in each regression hence there are two sets of regression summary statistics. For brevity, except for the satisfaction by facebook use interaction term, all scaled beta coefficients in the table are from the regression that included the self-esteem by facebook use interaction term. The pattern of significance of all other variables did not change when the satisfaction by facebook use term was entered in place of the self esteem by facebook use term. 23

25 Figure 3. Interaction of Facebook Use Intensity and Satisfaction with MSU Life on Bridging Social Capital Bridging Social Capital Low Satisfaction High Satisfaction Facebook Use Intensity Figure 4. Interaction of Facebook Intensity and Self Esteem on Bridging Social Capital Bridging Social Capital Low Self Esteem High Self Esteem Facebook Use Intensity 24

26 In model 2, bonding social capital was also significantly predicted by the intensity with which students used Facebook (scaled beta=.37, p<.0001). Other factors that related to bonding social capital were ethnicity (being white, scaled beta=.17, p<.01), year in school (scaled beta =.23, p<.001), living on campus (scaled beta=.13, p<.01), self esteem (scaled beta=.22, p<.01), and satisfaction with MSU life (scaled beta =.40, p<.001). General Internet use was not a significant predictor of bonding social capital, and the interactions between Facebook use and the two psychological measures were not significant. Overall, the included variables explained just less than a quarter of the variance in students' reported bonding social capital. Finally, we found the same strong connection between Facebook intensity and high school social capital in model 3 (scaled beta=.37, p<.001). Interestingly, general Internet use was a significant predictor of high school social capital (scaled beta=.26, p<.05). Ethnicity (being white, scaled beta=.23, p<.001) and self esteem (scaled beta=.30, p<.001) were the other significant variables in this regression, which overall explained 16% to 17% of the variance in the dependent measure. We further explored the Facebook - social capital relationship by examining whether various types of Facebook use, and the extent to which existing friends used Facebook, predicted the amount of each type of social capital (see Table 8). In Model 4 (Adj. R 2 =.16), results indicate that having more friends who also use Facebook (scaled beta=.32, p<.001), using Facebook to connect with offline contacts (scaled beta=.21, p<.05), and using Facebook for fun (scaled beta=.18, p<.05) were positively associated with bridging social capital, while using it to meet new people had a negative association (scaled beta=-.16, p<.01). These same factors did not explain bonding social capital well (Model 5, Adj. R 2 =.06), with only having more friends who use Facebook significant (scaled beta=.35, p<.01). In model 6 (Adj. R 2 =.13), high school social 25

27 capital was mainly explained by having friends using Facebook (scaled beta=.61, p<.0001), although as with bridging social capital, using Facebook for meeting new people exhibited a negatively association (scaled beta=-.16, p<.05). Table 8. Regressions Predicting Amount of Social Capital from Motivations for Facebook Use Model 4: Bridging Social Capital Scaled Model 5: Bonding Social Capital Model 6: High School Social Capital Scaled Beta Beta 1 P 2 Independent Variables Beta P P Scaled Intercept 3.83 **** 3.75 **** 3.80 **** On to Offline: Use FB to meet new people ** * Off to Online: Use FB to connect with offline contacts 0.21 * Use FB for fun, filling up free time or taking breaks 0.18 * Use FB to find out about events, trends, music, or get information Extent to which friends and contacts are using FB 0.32 *** 0.35 ** 0.61 **** N=260 F=10.67**** Adj R 2 =.16 1 Continuous factors centered by mean, scaled by range/2 2 *=P<.05, **=P<.01, ***=P<.001, ****=P<.0001 Discussion N=260 F=4.13 ** Adj R 2 =.06 N=260 F=8.51 **** Adj R 2 =.13 Returning to our original research question, which probed the relationship between use of Facebook an online social network serving a specific geographic area and social capital, we can definitively state that there is a positive relationship between certain kinds of Facebook use and the maintenance and creation of social capital. Although our methods do not allow us to make a causal argument, intensive Facebook use is a significant predictor of bonding, bridging, and high school social capital. Unlike other contexts that help members create or maintain social capital, such as exclusive social clubs, Facebook is open to all. Comparing members vs. nonmembers in our sample, we see no real difference in demographics, with the exception of class year and age 26