Spatially Bounded Online Social Networks and Social Capital:

The Role of Facebook

Nicole EllisonCharles Steinfield

Cliff LampeDepartment 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

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).

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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 2005. 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

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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 -- 78 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 email 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

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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 [computer-

supported 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

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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 email 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

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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 well-

suited 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

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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).

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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

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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 &

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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

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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 email 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

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Zoomerang (http://www.zoomerang.com), a commercial online survey hosting site, and was

fielded in April, 2006. We focused on undergraduate users and did not include faculty, staff, or

graduate students in our sampling frame. Two reminder emails 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

female34% (98)66% (188)

Age 20.1 1.64Ethnicity white

non-white87% (247)13% (36)

Income1 3.18 2.04Year in school2 2.55 1.07Home residence: in-state

out-of-state91% (259)09% (25)

Local residence: on campusoff campus

55% (157)45% (127)

Member of fraternity or sorority 08% (23) 1.01Hours of Internet use per day2 2 hours 56 min. 1:52Facebook 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 more2 1=first year, 2=sophomore, 3=junior, 4=senior3 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.

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• 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

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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 Intensity1

(Cronbach's alpha=0.83) -0.08 0.79About how many total Facebook friends do you have at MSU or elsewhere?0=10 or less, 1=11-50, 2=51-100, 3=101-150, 4=151-200, 5=201-250, 6=251-300,7=301-400, 8=more than 400 4.39 2.12In the past week, on average, approximately how many minutes per day have youspent 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 1.07 1.16Facebook is part of my everyday activity 3.12 1.26I am proud to tell people I'm on Facebook 3.24 0.89Facebook has become part of my daily routine 2.96 1.32I feel out of touch when I haven't logged onto Facebook for a while 2.29 1.20I feel I am part of the Facebook community 3.30 1.01I would be sorry if Facebook shut down 3.45 1.14

1 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

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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 Scales1 Mean S.D.

Use Facebook for filling up free time, taking breaks, fun(Cronbach's alpha=0.77) 3.60 0.83I use Facebook to fill up free time 3.43 1.03I use Facebook to take a break from doing my homework 3.59 1.05I browse Facebook just for fun 3.77 0.92

Use Facebook to find out about events, trends, music, or get information(Cronbach's alpha=0.75) 2.25 0.78I use Facebook to find out about things going on at MSU 2.59 1.07I use Facebook to keep up to date on current trends 2.01 1.04I use Facebook to find out about new music or movies 1.85 0.91I use Facebook to get useful information 2.55 1.10

Off to Online: Use Facebook to connect with offline contacts(Cronbach's alpha=0.70) 3.64 0.79I have used Facebook to check out someone I met socially 3.99 1.05I use Facebook to learn more about other people in my classes 3.26 1.20I use Facebook to learn more about other people living near me 2.86 1.22I use Facebook to keep in touch with my old friends 4.42 0.86

On to Offline: I use Facebook to meet new people(single item measure) 1.97 1.03

Critical mass of friends on Facebook(Cronbach's alpha=0.86) 4.07 0.71Many people I communicate with use Facebook 4.22 0.81The people I communicate with will continue to use Facebook in the future 3.82 0.82Of the people I communicate with regularly, many use Facebook 4.17 0.78

1 Individual items ranged from 1 = strongly disagree to 5 = strongly agree, scales constructed by taking mean ofitems.

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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 Resultsfor Self Esteem and Satisfaction with MSU Life Items

Factor Loadings1

Individual Items and Scales2 Mean S.D. Self EsteemSatisfaction

with MSU Life

Self Esteem Scale(Cronbach's alpha=0.87) 4.30 0.55I feel that I'm a person of worth, at least on anequal plane with others 4.50 0.60 0.80 0.05

I feel that I have a number of good qualities 4.54 0.57 0.76 0.03

All in all, I am inclined to feel that I am a failure(reversed) 4.27 0.86 0.74 0.10I am able to do things as well as most otherpeople 4.29 0.63 0.73 0.09I feel I do not have much to be proud of(reversed) 4.26 0.89 0.69 0.01

I take a positive attitude toward myself 4.17 0.75 0.76 0.27

On the whole, I am satisfied with myself 4.07 0.84 0.72 0.33

Satisfaction with MSU Life Scale(Cronbach's alpha=0.87) 3.55 0.74

In most ways my life at MSU is close to my ideal. 3.42 0.96 0.10 0.84

The conditions of my life at MSU are excellent. 3.54 0.91 0.12 0.87

I am satisfied with my life at MSU. 3.85 0.84 0.09 0.86So far I have gotten the important things I want atMSU. 3.74 0.81 0.12 0.79If I could live my time at MSU over, I wouldchange almost nothing. 3.18 1.05 0.11 0.66

1 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 ofitems.

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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).

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Table 5. Summary Statistics and Factor Analysis Resultsfor Social Capital Items

Factor Loadings1

Individual Items and Scales2 Mean S.D.

BridgingSocialCapital

BondingSocialCapital

High SchoolSocialCapital

Bridging Social Capital Scale(Cronbach's alpha=0.87) 3.81 0.53

I feel I am part of the MSU community 3.78 0.80 0.70 -0.24 0.13

I am interested in what goes on at MSU 3.98 0.64 0.73 -0.10 0.13

MSU is a good place to be 4.22 0.78 0.73 -0.12 0.18I would be willing to contribute money to MSUafter graduation 3.35 0.95 0.66 -0.04 0.13Interacting with people at MSU makes me wantto try new things 3.74 0.68 0.60 -0.04 0.15Interacting with people at MSU makes me feellike a part of a larger community 3.81 0.68 0.72 -0.09 0.23I am willing to spend time to support generalMSU activities 3.70 0.77 0.76 -0.10 0.16At MSU, I come into contact with new people allthe time 4.05 0.69 0.54 -0.17 0.13Interacting with people at MSU reminds me thateveryone in the world is connected 3.65 0.88 0.60 -0.07 0.04

Bonding Social Capital Scale(Cronbach's alpha=0.75) 3.72 0.66There are several people at MSU I trust to solvemy problems 3.22 1.01 0.17 -0.07 0.60If I needed an emergency loan of $100, I knowsomeone at MSU I can turn to 3.75 1.09 0.02 -0.18 0.76There is someone at MSU I can turn to for adviceabout making very important decisions 3.98 0.85 0.27 -0.09 0.76The people I interact with at MSU would be goodjob references for me 3.88 0.79 0.32 0.07 0.63I do not know people at MSU well enough to getthem to do anything important (reversed) 3.78 0.87 0.13 -0.23 0.61

High School Social Capital Scale(Cronbach's alpha=0.81) 3.77 0.67I'd be able to find out about events in anothertown from a high school acquaintance livingthere 3.59 0.88 0.20 -0.58 0.05If I needed to, I could ask a high schoolacquaintance to do a small favor for me 3.92 0.89 0.06 -0.86 0.18I'd be able to stay with a high schoolacquaintance if traveling to a different city 3.85 0.94 -0.02 -0.85 0.15I would be able to find information about a job orinternship from a high school acquaintance 3.58 0.89 0.11 -0.79 0.02It would be easy to find people to invite to myhigh school reunion 3.90 0.88 0.29 -0.56 0.14

1 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 ofitems.

19

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

20

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 andDependent Variables

Members(N=268)

Non-Members(N=18) Sig. of Difference

Independent Variables Mean or % S.D. Mean or % S.D.T-test or Chi-

Square1 P2

Gender: male (n=98)female (n=188)

92.86%94.15%

7.14%5.85% 0.18

Ethnicity: white (n=247)non-white (n=36)

93.93%91.67%

6.07%8.33% 0.25

Age 20.12 1.63 21.22 1.48 2.79 **Income 3.18 2.05 3.22 2.02 0.02Year in school 1.50 1.07 2.28 .96 3.00 **GPA 3.21 3.30 .71Home residence: in-state (n=259)

out-of-state (n=25)94.21%88.00%

5.79%12.00% 1.22

Local residence: on campus (n=157)off campus (n=127)

95.54%91.34%

4.46%8.66% 2.08

Fraternity/sorority member (n=23)nonmember (n=263)

100.00%93.16%

0.00%6.84% 3.12

Hours of Internet use per day 2:56 1:49 2:58 2:30 0.05Self esteem 4.29 .56 4.44 .52 1.16Satisfaction with life at MSU 3.57 .72 3.29 .96 -1.54Bridging social capital 3.82 .51 3.62 .73 -1.57Bonding social capital 3.74 .66 3.44 .62 -1.85High school social capital 3.79 .65 3.37 .90 -2.64 **

1 Chi-Square likelihood ratios for nominal variables and two-tailed T-test scores assuming equal variances forcontinuous variables2 *=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

21

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

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

My high

sch

ool

My re

latio

nship status

A ph

oto of ju

st m

e

My AI

M scree

n na

me

My cla

sses

A ph

oto with

me an

d ot

hers

My mob

ile num

ber

22

Figure 2. Who Has Viewed Respondents' Facebook Profiles

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

My high

sch

ool frie

nds

Peop

le in

my cla

sses

Other

friend

s

Tota

l stra

nger

at M

SU

Someo

ne I

met

at a

par

ty

Family

My re

siden

t men

tor

Tota

l stra

nger

ano

ther

cam

pus

Tota

l stra

nger

s no

t at a

sch

ool

My pr

ofes

sors

Administ

ratio

n

Law e

nfor

cemen

t

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

23

(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

Model 2:Bonding

Social Capital

Model 3:High School

Social Capital

Independent Variables1ScaledBeta2 P3

ScaledBeta P

ScaledBeta P

Intercept 3.80 **** 3.73 **** 3.57 ****Gender: male -0.02 0.07 -0.02Gender: female] 0.02 -0.07 0.02Ethnicity: white 0.08 * 0.17 ** 0.23 ***Ethnicity: nonwhite -0.08 * -0.17 ** -0.23 ***Income 0.04 0.07 0.08Year in school 0.00 0.23 *** -0.09State residence: in-state -0.05 -0.09 0.06State residence: out-of-state 0.05 0.09 -0.06Local residence: on campus -0.04 0.13 ** -0.06Local residence: off campus 0.04 -0.13 ** 0.06Fraternity/sorority member -0.01 -0.07 -0.02Not member of fraternity/sorority 0.01 0.07 0.02Hours of Internet use per day -0.03 -0.01 0.26 *Self esteem 0.20 0.22 ** 0.30 ***Satisfaction with life at MSU 0.66 **** 0.40 *** -0.02Facebook (FB) intensity 0.34 **** 0.37 **** 0.37 ***Self esteem by FB intensity4 -0.35 ** -0.32 -0.11Satisfaction by FB intensity -0.51 *** -0.26 -0.08

with self esteem by FB intensitywith satisfaction by FB intensity

N=269F=18.83 **** Adj R2=.44F=19.92 **** Adj R2=.46

N=269F=7.60 **** Adj R2=.23F=7.48 **** Adj R2=.22

N=269F=5.88 **** Adj R2=.17F=5.40 **** Adj R2=.16

1 Nominal factors expanded to all levels2 Continuous factors centered by mean, scaled by range/23 *=P<.05, **=P<.01, ***=P<.001, ****=P<.00014 Only one interaction term was entered at a time in each regression – hence there are two sets of regressionsummary statistics. For brevity, except for the satisfaction by facebook use interaction term, all scaled betacoefficients in the table are from the regression that included the self-esteem by facebook use interaction term. Thepattern of significance of all other variables did not change when the satisfaction by facebook use term was enteredin place of the self esteem by facebook use term.

24

Figure 3. Interaction of Facebook Use Intensity and Satisfactionwith MSU Life on Bridging Social Capital

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

-2

Facebook Use Intensity

Bri

dg

ing

So

cial C

ap

ital

Low SatisfactionHigh Satisfaction

+2

Figure 4. Interaction of Facebook Intensity and Self Esteemon Bridging Social Capital

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

-2

Facebook Use Intensity

Bri

dg

ing

So

cial C

ap

ital

Low Self Esteem

High Self Esteem

+2

25

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. R2=.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. R2=.06), with only having more friends who

use Facebook significant (scaled beta=.35, p<.01). In model 6 (Adj. R2=.13), high school social

26

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 fromMotivations for Facebook Use

Model 4:Bridging

Social Capital

Model 5:Bonding

Social Capital

Model 6:High School

Social Capital

Independent VariablesScaledBeta1 P2

ScaledBeta P

ScaledBeta P

Intercept 3.83 **** 3.75 **** 3.80 ****On to Offline: Use FB to meet newpeople -0.16 ** -0.12 -0.16 *Off to Online: Use FB to connectwith offline contacts 0.21 * 0.15 0.08Use FB for fun, filling up free timeor taking breaks 0.18 * 0.08 0.02Use FB to find out about events,trends, music, or get information 0.06 0.04 -0.03Extent to which friends andcontacts are using FB 0.32 *** 0.35 ** 0.61 ****

N=260F=10.67**** Adj R2=.16

N=260F=4.13 ** Adj R2=.06

N=260F=8.51 **** Adj R2=.13

1 Continuous factors centered by mean, scaled by range/22 *=P<.05, **=P<.01, ***=P<.001, ****=P<.0001

Discussion

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

27

(which is strongly correlated with class year). This is most likely due to the fact that Facebook is

a relatively recent phenomenon and we would expect more senior students to be less likely to

join. The high penetration, and lack of any systematic difference between members and non-

members suggests that Facebook is having broad appeal, is not excluding particular social

groups, and has not had a noticeable effect on students' grades (note: there is no correlation

between GPA and intensity of Facebook use).

Facebook constitutes a newer form of virtual socializing in which connections are

initially made offline and then migrated online, where they can be maintained easily and perhaps

deepened in part due to the depth of personal information provided by the site. Our participants

overwhelmingly used Facebook to keep in touch with old friends and to maintain or intensify

relationships characterized by some form of offline connection such as dormitory proximity or a

shared class. For many, Facebook provided a way to keep in touch with high school friends and

acquaintances. This was demonstrated through the fact that the most common information on

users' profiles was likely to be relevant for existing acquaintances trying to find them (e.g. their

high school), that nearly all users felt that their high school friends had viewed their profile, and

by respondents' self-reported types of use (connecting with offline contacts as opposed to

meeting new people).

This offline to online movement differs from much of the early work on computer-

mediated communication and virtual communities. Due in part to the structure of the site, which

blocks entry to those without a school email address and then places individuals into

communities based on their email address, as well as the intensely active social nature of a

28

college campus, Facebook embodies a geographically bounded context.1 The greater use of

Facebook for entertainment than for informational purposes at first seemed at odds with its role

in forming and maintaining social capital. However, even though this can suggest a passive

audience role, entertaining oneself via Facebook is fundamentally different then doing so

watching television, due to the increased activity necessitated by the site and the connectivity-

enhancing benefits.

Although we cannot say which precedes the other, Facebook does appear to play an

important role in the process by which students form and maintain social capital, with usage

associated with all three kinds of social capital included in our instrument. Higher scores on the

Facebook Intensity measure predicted increased levels of High School social capital, which

assessed the extent to which participants could rely on high school acquaintances to do small

favors. This kind of social capital speaks most clearly to the “strength of weak ties” outlined by

Granovetter (1973, 1982). College students who are able to connect with high school

acquaintances online will no doubt find it easier to keep in touch with these potentially useful

connections, who may be sources of new information and resources, though probably not close

emotional support.

Access to others who might provide close emotional support is expressed as bonding

social capital. We found that bonding social capital was predicted by high self-esteem,

satisfaction with MSU life, and intense Facebook use. Just as Facebook can be used as a low-

effort way to keep tabs on distant acquaintances, it can also be used to maintain close

relationships. For instance, in our pilot interviews, students discussed the “birthday” feature of

1 In May of 2006, Facebook began establishing company sites, and allowing members to choosedifferent networks to which they might belong. Nonetheless, college Facebook communitiesremain defined by those who have a school email account.

29

Facebook which allowed them to send greetings to friends on their birthday with minimal effort.

This kind of low-impact relational maintenance no doubt helps maintain strong bonds –

although, as Donath & boyd (2004, p. 80) point out, it may not necessarily increase the number

of strong ties an individual can maintain. Our findings suggest that the social affordances of tools

such as Facebook may in fact facilitate maintenance of strong bonds as well as the creation of

weak ones.

Our third dimension of social capital – bridging – assessed the extent to which

participants were integrated into the MSU community, their willingness to support the

community, and the extent to which these experiences broadened their social horizons or

worldview. Our findings suggest that those who use Facebook more intensely experience more

bridging social capital at MSU and potentially are more engaged with the MSU community.

Although our data do not speak to the mechanism through which this occurs, we can look to

participant reports about who is viewing their profile for insight. As depicted in Figure 2,

students report that the primary audience for their profile are high school friends and people they

know from an MSU context (such as a party or shared class, or “total strangers at MSU”).This

implies that highly engaged Facebook users are using Facebook to crystallize relationships that

might otherwise remain ephemeral. Haythornthwaite (2005) discusses the implications of media

that “create latent tie connectivity among group members that provides the technical means for

activating weak ties” (p. 125). Latent ties are those social network ties that are “technically

possible but not activated socially” (p. 137). Facebook enables participants to capitalize on weak

ties (such as “friending” a friend of a friend) and convert latent ties to weak ties (such as looking

up the profile of someone in a shared class and finding mutual areas of interest and possible

discussion topics). Facebook exposes users to new information both through these weak ties and

30

through the site itself, which has a mechanism for announcing parties and social events. These

weak ties will provide additional information and opportunities. Bridging social capital includes

dimensions such as “contact with a broader range of people; a view of oneself as part of a

broader group; and diffuse reciprocity with a broader community” (Williams, 2006). Because

bridging social capital provides benefits such as increased information and opportunities, we

suspect that participants who use Facebook in this way are able to get more out of their college

experience.

The consistent theme throughout our findings is that certain kinds of Facebook use

appear to facilitate the maintenance and formation of social capital of all kinds. Because the

college years are a unique developmental period in the life cycle and because the MSU Facebook

community is closely coupled with the geographically bounded MSU community, we are not

able to generalize these findings to other kinds of communities or social networking tools. It may

be that the positive outcomes linked to Facebook use discussed here are limited to this special

case in which the offline community is bounded spatially and the unique nature of the user

population (undergraduate students). However, the size of Facebook’s user base (7.5 million)

and the fact that it is currently being rolled out to other geographically-bound groups points to

the importance of empirical assessment of Facebook’s effects. Facebook may facilitate making

new friends, but also keeping in touch with old acquaintances – an extremely useful activity for

members of industry organizations as well as college students. As the old adage goes, Facebook

may help students and others accrue social capital riches as they “make new friends but keep the

old.” Rather than experiencing an impoverished social network, certain kinds of Facebook use

may allow users to accrue new silver while keeping old gold. However, students seem to gain

31

more when these new friends are based on some offline connection, as evidenced by the negative

relationship between using Facebook to meet new people and bridging social capital.

Of special interest to Internet researchers is the way in which Facebook use seemed to

support a “poor get richer” hypothesis, as opposed to the “rich get richer” findings reported in

other contexts (Kraut et al., 2002). One of our most interesting, and potential important, findings

is the special role Facebook seems to play in reducing barriers to participation among students

who suffer from low self esteem. We found that low self-esteem students who do use Facebook

more intensely are just as likely to have bridging social capital as their high self-esteem peers.

However, low self-esteem students who don't use Facebook intensely do not score as highly on

the bridging social capital measure, suggesting that they are not reaping the same benefits as

their Facebook-using peers. Facebook makes a significant difference for students who express

lower satisfaction with life at MSU, enabling them to accrue more bridging social capital. It also

seems to reduce barriers here as well, since otherwise we might expect dissatisfied students to

score lower on this measure.

Limitations to this study include the fact that we examined only one community, limiting

our ability to generalize to other contexts. Because we used a one–time survey, we cannot

establish causality. Additionally, our ability to assess the effects of Facebook membership were

hampered by the extremely low incidence of non-members in our sample, as was our ability to

test the effects of Facebook on different ethnic groups or international students. Because our

survey used self-reported measures of Facebook use, there is a chance respondents may have

mis-reported behavior or demographic information. Future research should pair survey data with

actual measures of use, such as information collected from actual profiles on the Facebook site.

32

Conclusions

This study provides a view of the role of Facebook on campuses that is very different

from those reported in the popular press. Our empirical results contrast with the anecdotal

evidence dominating the popular press in that we found social capital benefits associated with

certain kinds of Facebook use. Although there are clearly some image management problems

experienced by students as reported in the press and the potential for privacy abuses does exist,

our findings demonstrate a robust connection between Facebook usage and indicators of social

capital. In short, Facebook users can benefit from their online practices.

The strong linkage between Facebook use and high school connections suggests how

online social networks help maintain relations as people move from one offline community to

another. It may facilitate the same when students graduate from college, with alumni keeping

their school email address and using Facebook to stay in touch with the college community.

Such connections could have strong payoffs in terms of jobs, internships, and other

opportunities. Colleges may want to explore ways to encourage this sort of usage.

Finally, our findings do suggest that participants in bounded online communities – e.g.

where participants have a common offline affiliation, especially one that would lead to

opportunities for face-to-face meetings – are doing fundamentally different things than those

reported in the early virtual community literature. They are using the online channel less to meet

new people than to intensify and solidify relationships that started offline. This has important

theoretical implications for theories of computer-mediated communication and social networks.

33

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