Social capital: the benefit of Facebook friends

Social capital: the benefit of Facebook ‘friends’

Kevin Johnston*, Maureen Tanner, Nishant Lalla and Dori Kawalski

Information Systems Department, University of Cape Town, South Africa

(Received 28 July 2009; final version received 9 December 2010)

This research investigated the role Facebook use plays in the creation or maintenance of social capital among university students in South Africa. Data were collected using questionnaires completed by over 800 students from 7 universities. The questionnaire was obtained from a study conducted in Michigan State University (Ellison N.B., Steinfield, C., and Lampe, C., 2007. The benefits of Facebook ‘‘Friends’’: social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12(4), 1143–1168.). Empirical research has linked social capital to many positives in society, such as improved mental and physical health, economic well- being, etc. Thus, social capital is important for the success of civil society. This research examined the relationships between Facebook use and the formation and maintenance of social capital amongst university students. The study also examined factors specific to the South African context and drew comparisons to the results of the original study. Analysis of the results suggests a strong association between the intensity of Facebook use and perceived bridging, bonding and maintained social capital. This paper broadens the understanding of Facebook usage by introducing the dimensions of race and age. Facebook usage was found to interact with measures of psychological well-being, suggesting that it might be beneficial to students experiencing low self-esteem and low life satisfaction.

Keywords: Facebook, social capital, South Africa, intensity

1. Introduction

The internet enabled a communication revolution, allowing users to send and retrieve information irrespective of geographical location, thus changing the way human beings live, work and communicate (O’Murchu et al. 2004). As the internet became an integral part of life, researchers became interested in its effects on social exchange and relationships (Williams 2006).

Social networking is based on the idea that society exists as a structured set of relationships between people (Toomey et al. 1998). With the arrival of web 2.0 technologies, a new wave of online social network- ing tools and services emerged. These include weblogs, social network sites, forums and instant messaging. Social network sites attracted millions of users includ- ing the attention of academic and industry researchers (Boyd and Ellison 2007).

There are currently many social network sites, offering a variety of services targeted at diverse audiences across the globe (Boyd and Ellison 2007). Online social network sites bring together a vast number of people who share common interests, views and goals (Boyd and Ellison 2007). These new forms of social networking impact the development and maintenance of social capital (DiMaggio et al. 2001).

Facebook is a social networking site of particular interest to researchers due to its heavy usage patterns and its technological capabilities, which allow for the bridging of online and offline relationships (Ellison et al. 2007).

This empirical research replicates a study from the Michigan State University (MSU) (Ellison et al. 2007), which assessed the intensity of Facebook use and its association with social capital. This research broadens the understanding of Facebook usage by introducing the dimensions of race and age across a range of universities in South Africa. Network theorists argue that understanding social capital requires a fine- grained analysis of the specific quality and configura- tion of network ties (Adler and Kwon 2002).

The paper begins by introducing concepts of social networking and social capital. The research methodol- ogy is then explained, followed by the analysis of the data. The implications of the results are discussed, and the paper is concluded by highlighting key aspects of the study.

2. Review of literature

2.1. Online social networking

Online social networks are defined as virtual commu- nities which interact and pool resources through

*Corresponding author. Email: [email protected]

� 2013 Taylor & Francis

Behaviour & Information Technology, 2013 Vol. 32, No. 1, 24–36, http://dx.doi.org/10.1080/0144929X.2010.550063

computer-mediated relationships (Toomey et al. 1998). Often, these networks consist of people who share common affinities or interests and may or may not be separated geographically (Boyd and Ellison 2007). Social networking has changed as a result of the improvement and transformation of communication technologies, primarily the internet. Bargh and McKenna (2004) state that the internet is special as it combines into one tool, features of many previous breakthroughs: person-to-person communication (such as telephones), mass medium (such as televisions) and information resources (such as libraries). While the internet was initially assumed to be merely a standardised mean of accessing information, current online social networking tools such as social network sites have allowed individuals to connect with each other more effectively than was anticipated (Weaver and Morrison 2008).

An online social network site can be defined as a set of web-based services that allows individuals to ‘(1) construct a public or semi-public profile within a bounded system, (2) articulate a list of other users with whom they share a connection, (3) view and transverse their list of connections and those made by others within their system’ (Boyd and Ellison 2007, p. 221). Many of these social network sites are primarily used to articulate existing social networks rather than expand networks (Boyd and Ellison 2007), thus reflecting real-life social relationships fairly accurately (Ellison et al 2007).

2.2. Social capital

Social capital refers to resources accumulated from various relationships (Coleman 1988) and lies in the structure of relationships within which the actors are located (Portes 1998). It can be considered as a by- product of social relationships resulting from social exchanges in structured social networks (Islam et al. 2006), and promotes co-operation between individuals (Fukuyama 2001). Social capital can be broken into two classes, namely cognitive and structural. Cognitive social capital is linked to personal aspects such as beliefs, values, norms and attitudes (Islam et al. 2006). It is also a by-product of cultural norms like religion, tradition and shared historical experiences (Fukuyama 2001). Structural social capital is the outwardly visible features of social organisations such as patterns of social engagement or density of social networks (Islam et al. 2006). The structural class reflects the strength of associational links, density of social associations and indicators of social interactions (Islam et al. 2006). Figure 1 outlines the forms of social capital relevant to this study. These relate to bridging, bonding (Putnam 2000) and maintained

social capital (Ellison et al. 2007) and are all part of the cognitive social capital class.

2.2.1. Bridging social capital

Bridging social capital focuses on external relations (Adler and Kwon 2002) and refers to the ‘weak ties’ between individuals (Putnam 2000). These ‘weak ties’ usually form between individuals of different ethnic and occupational backgrounds (Islam et al. 2006) and can cut across geographic and socio economic distance (Carter and Maluccio 2003). ‘Weak tie’ relationships are considered provisional and lack depth (Williams 2006), thus making bridging social capital inherently heterogeneous (Putnam 2000). Bridging social capital between individuals provides useful information and new perspectives. It expands social horizons but does not provide much emotional support (Granovetter 1983, Williams 2006, Ellison et al. 2007). Individuals with ‘weak ties’ or bridging social capital tend to have a broader set of information and access to opportu- nities. This phenomenon is known as the ‘strength of weak ties’ (Granovetter 1983). Donath and Boyd (2004) suggested that social network sites could increase the formation and maintenance of ‘weak ties’ or bridging social capital because the costs of use are low. Solidarity can also emerge from weak ties and can thus otherwise bridge diverse racial groups as in the case of South Africa (Adler and Kwon 2002).

2.2.2. Bonding social capital

In contrast, bonding social capital exists between family members, close friends and other close relations and focus on internal ties between actors (Morrow 2001, Adler and Kwon 2002). These relations are generally homogenous and inclusive, existing between strongly knit, emotionally close relationships (Williams 2006, Ellison et al. 2007). Bonding relationships provide emotional support and a way of transmitting behavioural norms between individuals in the relation- ship (Islam et al. 2006). The type of relationships and structures within a social network determines the types of social capital formed in these networks (Williams 2006). ‘Strong tie’ relationships or bonding social capital does not provide links to individuals of differing backgrounds (Williams 2006).

Bonding social capital is closely related to the Chinese concepts of ‘guanxi’ and ‘renqing’. Guanxi is embedded in daily social practices of people and relates to personal connections and relationships (Smart 1993, Chung 2006). Guanxi is essential to the completion of tasks in social life, and has both positive (such as reciprocity and gifts) and negative (such as bribes and nepotism) connotations (Smart

25Behaviour & Information Technology

1993, Gold, Guthrie and Wank 2002, Chung and Hamilton 2003). This study only focuses on the positive aspects of guanxi.

2.2.3. Maintained social capital

Ellison et al. (2007) established a third type of social capital called ‘Maintained social capital’. Maintained social capital is created when individuals maintain connections to their social networks having progressed through life changes (Bargh and McKenna 2004, Ellison et al. 2007). The use of technology can assist people to maintain relationships threatened by changes in geographical location (Bargh and McKenna 2004). The terms ‘friendsickness’ refers to the anguish caused by loss of contact with friends (Paul and Brier 2001). ‘Friendsickness’ is usually caused when school students move away to tertiary learning institutions (Paul and Brier 2001). Research shows that university students use email and instant messaging services to stay in touch with old high school friends (Ellison et al. 2007). Proximity does not affect these relationships; however, the level of communication does affect the relationship (Oswald and Clark 2003).

2.2.4. Benefits of social capital

Social capital has been shown to be a forecaster of school attrition, academic performance, physical and mental health, children’s intellectual development, sources of employment, juvenile delinquency and its prevention, and economic development (Coleman 1988, Portes 1998, Putnam 2000, Mcckenzie et al. 2002, Ellison et al. 2007).

Generally, when social capital is low within a community, there tends to be greater social disorder and more distrust amongst participants (Helliwell and Putnam 2004). However, with greater social capital comes a general commitment to collective action which generally results in a positive effect with regard to interaction (Ellison et al. 2007).

2.3. Negative social capital

In spite of the advantages of social capital, negative aspects still prevail (Portes 1998), as people tend to divide the world between friends and enemies. For instance, social capital might lead to the creation of hate groups as can sometimes be seen on Facebook (Fukuyama 2001). Strong ties between members of a group can exclude outsiders’ access to a group (Portes 1998). Weaker group members can make excess claims on stronger members (the free-riding problem) (Portes 1998). Participation in a group generally dictates certain levels of conformity (Portes 1998), and this can restrict individual freedom. Situations where group solidarity is formed by common experiences are termed downward levelling norms, individual success stories undermine group cohesion (Portes 1998).

2.4. Measurement of social capital

The concept of social capital is elusive, both in terms of its meaning and measurement (Islam et al. 2006, Williams 2006). There is no consensus on the measurement of social capital (Fukuyama 2001, Williams 2006). Researchers have to identify observa- ble variables and develop methods to use those

Figure 1. Social capital.

26 K. Johnston et al.

variables as proxies for social capital (Islam et al. 2006). Williams (2006) developed tools to measure internet social capital known as Internet Social Capital Scales or ISCS, which have been validated in previous studies (Valenzuela et al. 2008, Ellison et al. 2007) and were used in this study. These scales provide clarifica- tion of social capital and its formation online and offline, as well as the tradeoffs between the two (Williams 2006). The relationship between Facebook use and social capital may be explored by examining individuals’ self-esteem (Rosenberg 1965) and satisfac- tion with life (Pavot and Diener 1993) two validated measures of subjective well-being.

2.5. Technology and social capital

Some researchers say that the internet diminished social interactions regarding face-to-face exchanges (Bargh and McKenna 2004). However, it can be argued that changing technology changes forms of associations (Fukuyama 2001). The ‘uses and gratifica- tions’ theory suggests that ‘the particular purpose of individuals within communication settings will deter- mine the outcome of the interaction’, regardless of the type of communication channel used (Bargh and McKenna 2004, p. 578). Another viewpoint proposes that elements of internet communication impact interaction outcomes, and the impacts depend on the social context (Bargh and McKenna 2004).

Wellman et al. (2001) argued that online interac- tion provides new means of communication between parties, as well as supplementing or replacing physical interactions, thereby strengthening relationships. One reason for the initial confusion of the effects of the internet and social capital is the lack of controlled longitudinal research (Williams 2006). Online social network tools might be useful to individuals who generally struggle to form and maintain both strong and weak ties. Some studies demonstrated that the internet might help individuals having low psycholo- gical well-being and few ties to friends and neighbours (Bargh and McKenna 2004). Barriers to interactions can be lowered and self-disclosure encouraged through some form of computer-mediated communication (Tidwell and Walther 2002, Bargh and McKenna 2004).

2.6. The South African context

No study of South Africa can be complete without some understanding of the social context of the country. Apartheid in South Africa actively oppressed and humiliated non-white people, limiting their access to education, and ability to accumulate and use assets (Carter and May 2001). All citizens were racially

classified and issued identification numbers that con- tained racial classification. South African governments of the 1920–1990s used laws and power to separate and exclude non-white people. Non-white South Africans were repeatedly degraded, ill treated, and informed of their inferior status (Ramphele 2008). People of different racial classifications were legally forbidden to marry, socialise, live, play, learn, or be buried together. South Africa held its first democratic election in 1994. Fifteen years later, ‘the persistent matter of race and identity’ continue to permeate all aspects of life and plague South Africans (Boesak 2009, p. 9). South Africa continues to be a divided nation, a first world part mainly populated by whites, and a third world part populated by blacks (Adato et al. 2006) and this distorts most statistics (Waddock 2007). South Africans have a life expectancy of 51.5 (the average for Africa was 53.9), an adult literacy rate of 88 (Africa 63.3), and GDP per capita $9.757 (Africa $2.729) (Klugman 2009). In 2001, South Africa had a GENI coefficient of 0.73 and is ‘one of the most unequal societies in the world, more than half of all South Africans live in poverty, more than 10% of South Africans live in absolute poverty, and the situation is getting worse’ (Hall 2007, p. 21). South Africa has a population of 49.32 million, of which 52% were females, 79% of the population were black, and 9% white (Lehohla 2009).

The Digital Divide phenomenon which is prevalent in South Africa is defined as ‘the gap between those who can effectively use or have access to new information and communication tools, such as the internet, and those who cannot’ (Mutula 2005, p. 123). The digital divide can also exist between gender, physical disability, racial and age differences (Singh 2004). These differences are especially prominent in South Africa due to its apartheid legacy (Singh 2004).

3. Hypotheses and research questions

Table 1 summarises the hypotheses from the paper by Ellison et al. (2007), which were replicated in this study. Seven exploratory questions were constructed to examine specific aspects relating to the South African context. Three questions examined the role race played in the relationship between Facebook use intensity and the three forms of social capital. Similarly, three questions examined the role age played in the relation- ship between Facebook use intensity and the three forms of social capital. The seventh question examined the demographics of Facebook members versus non- Facebook members amongst South African university students. All questions were submitted to and approved by the University Ethics committee.

Behaviour & Information Technology 27

4. Methodology

The underlying philosophy for this research is positivist. This study made use of primary data sources retrieved first hand. Quantitative data were collected through questionnaires obtained from a previous study (Ellison et al. 2007). The original questionnaire was trimmed down due to its length, in consultation with the original authors. The question- naire is available for future use. Various statistical techniques were used to analyse the data. Most of the analytical methods were obtained from the study by Ellison et al. (2007). Additional demographic data (e.g. ethnicity, gender, etc.) were collected through the questionnaires. All questionnaires were returned in a two-week window, implying that a snapshot of the current situation was taken. The data acquired were used in an attempt to support or reject the hypotheses.

A random sample of students was selected from seven tertiary institutions within South Africa (Uni- versity of Cape Town, University of Witwatersrand, University of Fort Hare, Cape Peninsula University of Technology, University of Johannesburg, Stellenbosch University, and University of Western Cape). Permis- sion to distribute the questionnaire was obtained prior to distribution. Eight hundred and twenty-three responses were captured. The raw data were cleaned and formatted, using Microsoft Excel 2007, so that it could be used in Statistica. All partially completed responses were removed before analysis, reducing the number of valid responses to 572, of which 67% (383) were members of Facebook.

5. Data analysis

Five-point Likert scales were extensively used in the questionnaire. Various measures and constructs were obtained from the original study. These were used in assessing demographics, general life satisfaction at university, self-esteem, forms of social capital and intensity of Facebook use. These measures were then

used in building regression models to assess the impact of Facebook use on social capital.

Two sets of regressions were used to build models to predict statistics for each form of social capital. The first regression was used as a comparison with the original study. The second regression included ethni- city and age variables in order to assess age and ethnicity factors in the social capital models. Interac- tion terms used in the regression analysis were constructed by multiplying the variables, for example: ‘self-esteem by Facebook Intensity’ was constructed by: (self-esteem) 6 (Facebook intensity).

5.1. Chi-squared goodness-of-fit test

The chi-squared goodness-of-fit test was used to assess that the sample was an accurate representation of the population. The most recent figures regarding student enrolment in South African universities was used (HEMIS 2007). It is assumed that university demo- graphics have not changed significantly since then, and that these figures are still representative of general university demographics. The chi-squared test con- firmed that the sample used was a good representation of South African students both in terms of race and gender.

5.2. Measures of Facebook usage

5.2.1. Facebook intensity

The Facebook intensity scale attempted to obtain a measure of Facebook intensity other than measures of frequency or duration of Facebook use (Ellison et al. 2007). The construct consisted of two questions (13 and 14) regarding Facebook use, to assess how actively involved respondents are on Facebook, as well as six Likert-scale questions (sub questions of question 17), which assessed respondents’ attitudes towards Face- book. The attitudinal questions related to the extent to which a respondent feels emotionally connected to

Table 1. Hypotheses from Ellison et al. (2007).

H1: Intensity of Facebook use will be positively associated with individuals’ perceived bridging social capital. H2: Intensity of Facebook use will be positively associated with individuals’ perceived bonding social capital. H3a: The relationship between quantity of Facebook use and bridging social capital will vary depending on the degree of a

person’s self-esteem. H3b: The relationship between quantity of Facebook use and bridging social capital will vary

depending on the degree of a person’s satisfaction with life. H4a: The relationship between quantity of Facebook use and bonding social capital will vary depending on the degree of a

person’s self-esteem. H4b: The relationship between quantity of Facebook use and bonding social capital will vary

depending on the degree of a person’s satisfaction with life. H5: Intensity of Facebook use will be positively associated with individuals’ perceived maintained social capital.

28 K. Johnston et al.

Facebook, as well as assessing how significant a role Facebook plays in a participant’s regular activities. Table 2 summarises statistics associated with the Facebook Intensity construct. The construct yields a Cronbach’s alpha of 0.84, indicating a high reliability of the sub-items in supporting the construct.

The analysis indicates that time spent using Facebook per day (Q. 14) fell within the 10– 30 minute category, and that the average South African student indicated he/she has between 100 and 150 friends. The MSU students’ time averages fell within the 10–30 minutes, while the average number of friends ranged between 150 and 200. Researchers at Sheffield Hallam University and the University of Liverpool have found that most people have five-core online friends (the same number they have offline) despite claiming 150 or 200 online friends (Lim 2007). The Likert-scale questions provided rather neutral results, with mean values around three. However, the

standard deviation of all of these items was relatively high (i.e. above 1).

5.2.2. Facebook usage: elements in profile and percep- tions of who has viewed profiles

Respondents were asked to indicate which profile elements they included when developing their Face- book profile (Figure 2). Respondents were also asked to indicate who they thought had viewed their Face- book profile (Figure 3). These items are valuable in assessing Facebook use regarding the development of new relationships or the maintaining of existing relationships.

Contact details were the most common profile element included (77%), and ‘My classes’ the least common (10%). More than 70% of MSU students included university classes in their profiles (Ellison et al. 2007).

Table 2. Summary statistics for Facebook intensity (N ¼ 383).

Question Individual items and scale Mean SD

Facebook intensity (Cronbach’s alpha ¼ 0.840) 3.02 0.97 Q. 13 About how many total Facebook friends do you have? 3.17 2.31

0 ¼ 10 or less, 1 ¼ 11–50, 2 ¼ 51–100, 3 ¼ 101–150, 4 ¼ 151–200, 5 ¼ 201–250, 6 ¼ 251–300, 7 ¼ 301–400, 8 ¼ more than 400

Q. 14 In the past week, on average, approximately how many minutes per day have you spent on Facebook?

1.69 1.44

0 ¼ less than 10, 1 ¼ 10–30, 2 ¼ 31–60, 3 ¼ 1–2 hours, 4 ¼ 2–3 hours, 5 ¼ more than 3 hours

Q. 17 1. Facebook is part of my everyday activity. 3.03 1.31 2. I am proud to tell people I am on Facebook. 3.53 1.00 3. Facebook has become part of my daily routine. 3.07 1.27 4. I feel out of touch when I haven’t logged onto Facebook for a while. 2.74 1.37 5. I feel I am part of the Facebook community. 3.36 1.08 6. I would be sorry if Facebook shut down. 3.58 1.23

Notes: Individual items were first standardised before taking a mean to create a scale. Unless provided, response categories ranged from 1 ¼ strongly disagree to 5 ¼ strongly agree.

Figure 2. Profile elements.

Behaviour & Information Technology 29

Figure 3 shows who respondents perceived have viewed their profiles, ‘High school friends’ (88%) and ‘Friends other than high school friends’ (85%) were the most selected responses.

5.2.3. Use of Facebook to meet new people vs. connect with existing offline contacts

The purpose of this construct is to ascertain whether respondents are inclined to use Facebook to find new people online or to find contacts with whom they already have an offline relationship.

Table 3 shows Cronbach’s alpha for the construct ‘Offline to online: use of Facebook to connect with offline contacts’ is 0.60 and is not considered to be highly reliable. The MSU study yielded a Cronbach’s alpha of 0.70 and was considered to be reliable in supporting the construct.

The single item measure ‘On to offline: use Face- book to meet new people’ has a mean of 2.55. The MSU study mean was 1.97 which is lower than the current study’s finding. The question ‘I use Facebook to keep in touch with my old friends’ has a particularly high mean of 4.47 and a low standard deviation (0.89), indicating that the majority of Facebook members agreed with this statement.

5.3. Measures for psychological well-being

Self-esteem was measured using the Rosenberg self- esteem scale (Ellison et al. 2007) in question 20. The scale is made up of seven items, posed on a five-point Likert-scale. The scale exhibited high reliability with a Cronbach’s alpha ¼ 0.81 (Table 4).

The satisfaction with university life was adopted from the Satisfaction with Life Scale (Ellison et al. 2007) in question 21. The scale exhibited high reliability with a Cronbach’s alpha ¼ 0.82.

5.4. Measures of social capital

The three types of social capital were measured by adapting existing scales. Items which capture internet-

specific social capital were also included (Ellison et al. 2007). The factor loadings analysis was calculated for all the social capital items. The results show that the social capital items actually represent three distinct factors.

5.4.1. Measure for assessing bridging social capital

This measure assessed the degree to which respondents experience bridging social capital (Ellison et al. 2007), using Williams’ (2006) bridging social capital subscale. The scale exhibited high reliability with a Cronbach’s alpha ¼ 0.86.

5.4.2. Measure for assessing bonding social capital

This measure assessed the extent to which respondents experienced bonding social capital. Bonding social capital makes use of five items from the bonding subscale developed and validated by Williams (2006).

Table 3. Summary statistics for Facebook use for prior contacts and meeting new people (N ¼ 383).

Questions Individual items and scales Mean SD

Off to online: use Facebook to connect with offline contacts (Cronbach’s alpha 0.60)

3.37 0.81

Q. 16 1. I have used Facebook to check out someone I met socially.

3.57 1.33

2. I use Facebook to learn more about other people in my classes.

2.81 1.26

3. I use Facebook to learn more about other people living near me.

2.64 1.29

4. I use Facebook to keep in touch with my old friends.

4.47 0.89

On to offline: I use Facebook to meet new people (single-item measure)

2.55 1.45

Notes: Individual items ranged from 1 ¼ strongly disagree to 5 ¼ strongly agree, scales constructe

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