Time Spent on Social Networking Sites: Understanding User Behavior and Social Capital

■ Research Paper

Time Spent on Social Networking Sites:Understanding User Behavior andSocial Capital

Tsung-Sheng Chang* and Wei-Hung HsiaoDepartment of Information Management, National Chung Cheng University, Min-Hsiung, Chia-Yi, Taiwan

This study uses the amount of time users spend on social networking sites (SNSs) todifferentiate user groups and investigates the following three issues: (1) the most commonbehavior of different groups when using SNS; (2) whether users have different perceptionsof their social capital on SNSs versus in real-life environments; and (3) whether there aredifferences in the perceived social capital of different groups. This study discovered thatusers have different user behavior depending on their amounts of usage. In particular,heavy users tend to be willing to share information and often use application programsassociated with SNSs. With regard to perceptions of social capital, the study found thatdifferent groups have somewhat different ideas as to what constitutes social capital. Wesummarize a novel individual social capital systematic behavior and discuss the practicalimplications of this work and suggestions for future research. Copyright © 2013 JohnWiley & Sons, Ltd.

Keywords social networking; social networking sites; social capital; online behavior; usercharacteristics

INTRODUCTION

Social networking sites (SNSs) are currently themost popular Web application services and en-able users to engage in online communicationand information sharing with friends or socialgroups (Governatori and Iannella, 2011). Face-book and Twitter are among the most well-known SNSs, with a vast numbers of users,

although there is considerable competition in thismarket. With the rapid growth of SNSs, both theInternet behavior and preferences of users haveevolved. Among Internet users in the USA, 65%online adults use SNS (Madden and Zickuhr,2011), which is more than those who use otheronline services, whereas approximately one-halfof European Internet users use SNS (EuropeanCommission, 2011). In addition, SNSs are alsoattracting many young users in emergingnations, and the number of SNS users in suchcountries is increasing rapidly (boyd, 2008).According to a 2010 market research report

*Correspondence to: Tsung-Sheng Chang, Department of InformationManagement, National Chung Cheng University, Min-Hsiung, Chia-Yi621, Taiwan.E-mail: [email protected]

Received 9 July 2012Accepted 18 December 2012Copyright © 2013 John Wiley & Sons, Ltd.

Systems Research and Behavioral ScienceSyst. Res. 31, 102–114 (2014)Published online 28 February 2013 in Wiley Online Library(wileyonlinelibrary.com) DOI: 10.1002/sres.2169

published by ComScore, in the USA, people nowspend more time using Facebook than Google(AFP.Com, 2010). We can conclude that socialnetworking has already become the popular on-line activity of most people.The tremendous popularity of SNSs derives

from the fact that they allow people to maintainrelationships with friends, as well as make newones. This gives users a high degree of self-esteem and satisfaction, and provides servicechannels that enable the development of individ-ual social capital (Ellison et al., 2007), which canbe seen as a network of relationships that relyon reciprocity and trust (Lin, 1999). These net-works can have many members, each with theirown relationships and social systems, and thesecan be used to explain an individual’s socialcapital (Nahapiet and Ghoshal, 1998, Adler andKwon, 2002; Mathwick et al., 2008). Wellmanet al. (2001) noted that when an individualengages in more frequent communication withother members in the social network, then thiswill transform their social capital. The questionthus arises as to whether the social capital ofusers who spend large amounts of time usingSNS gives them better relationships or benefitsthan the social capital of ordinary users. Burkeet al. (2010, 2011) and Ellison et al. (2011) notedthat users who spent more time on an SNS havemore friends and concluded that such sites canhelp people to build and maintain relationships.Moreover, they proposed that people who useand do not use SNS have the same individualsocial capital, which implies that there are nodifferences with regard to the social capital thatpeople have in virtual and real-life environments.However, White (2002) pointed out that socialcapital is a multidimensional construct, whichvaries depending on different types of behavior.Gilbert and Karahalios (2009) noted that SNSsare virtual environments and that not every oneof a person’s real-world friends may have anSNS account. Moreover, some people may havemany different SNS accounts, and users mayemploy SNS to construct different types of socialcapital in their relationships (Donath and boyd,2004). Huvila et al. (2010) compared social capitalin real life and a virtual world, Second Life, andtheir respondents stated that it is easier to meet

friends in real life and to have more opportunitiesfor face-to-face interactions. In addition, Guo andGong (2011) explored individual wealth differ-ences in a virtual and the real one and suggestedthat future research should examine how therelationships formed in both environments differ.They also found that there are differences inusers’ perceptions of social capital due to differ-ences in the SNS and real-world environments.Burke et al. (2010, 2011), Ellison et al. (2011) andHuvila et al. (2010) all raised the question ofwhether there are any differences in the individ-ual social capital that arises on an SNS and in reallife. However, to the best of the authors’ know-ledge, no studies have yet been published thatconsider this question and attempt to explainthe relationship between the social capitalacquired in real life and on an SNS.

In addition, according to Riva et al. (2003),people who use the Internet for differentamounts of time will have different behaviorsand characteristics. Although some past researchsought to understand what users do on SNSs—for instance, Hargittai and Hsieh (2010) investi-gated different SNS’s social behaviors amongstudents and Miller et al. (2010) compared theFacebook and MySpace user behavior of under-graduate students—there is still a lack of researchon differences in SNS user behavior and their re-lation to the amount of time spent using suchsites. If we can gain a better understanding ofuser behaviors or motivations with regard toSNSs, then this information can provide a basisfor the planning and development of bettere-commerce systems (Lu and Lin, 2002; Amieland Sargent 2004; Hong et al., 2006). The issueof how SNS use affects individual perceptionsof social capital is currently a major academicresearch topic (e.g. Steinfield et al., 2008; Ji et al.,2010; Choi et al., 2011). Choi and Scott (2011)suggested that research should investigate therelationship between the use of SNS and socialcapital by adopting various perspectives. On thebasis of the foregoing discussion, we use theamount of SNS usage to differentiate usergroups, as this can then shed light on differencesin user behavior and social capital. The followingare research questions that are investigated inthis study:

Syst. Res. RESEARCH PAPER

Copyright © 2013 John Wiley & Sons, Ltd. Syst. Res. 31, 102–114 (2014)DOI: 10.1002/sres

Time Spent on Social Networking Sites 103

(1) What differences in user behavior exist amonggroups with different amounts of time spentusing SNS?

(2) Are there differences in SNS and real-lifeperceived social capital among members ofgroups that spend the same amount of timeusing SNS?

(3) Are there differences in SNS and real-lifeperceived social capital among members ofgroups that spend different amounts of timeusing SNS?

We attempted to determine the actual SNS usebehavior of users in Taiwan. Taiwan is part of theGreater China market, which includes MainlandChina, Hong Kong and Macau. Thus, the resultsobtained in this study can be extrapolated to thislarger market and thus have considerable refer-ence value in practice.

LITERATURE REVIEW

Behavioral Characteristics of SocialNetworking Sites Users

Investigating the behavior of Internet users is aninterdisciplinary research topic. For instance,Casale and Fioravanti (2011) studied students’use of Internet in the context of psychosocialhealth, whereas Lykourentzou et al. (2012) inves-tigated the user behavior on Wiki sites operatedby businesses and proposed some specific impli-cations for managers. People can employ SNSto engage in real-time online communicationand information sharing with friends or socialgroups, and two main research frameworks arecurrently used by academic researchers to inves-tigate SNS user behavior, using clickstream dataand questionnaires.

The first involves the use of computer programsto collect clickstream data, followed by statisticaltreatment to analyse user behaviors (Benevenutoet al., 2009; Schneider et al., 2009), with theseincluding searching, viewing video or photos,making scrapbooks, posting testimonials, sendingmessages, taking part in communities and updat-ing profiles. Clickstream data consists of thebrowsing and user traffic data collected from

websites, and researchers can thus use largeamounts of data to analyse user behaviors via anumber of statistical operations. In addition, vanden Poel and Buckinx (2005) suggested that theanalysis of clickstream data can allow users’ web-site activities to be classified in detail, which canthen be used to infer different behaviors. As a con-sequence, this method provides a highly scientificbasis for data classification in this context.

The other method is the use of questionnaires,which can produce two types of results. One typeis exemplified by Valenzuela et al. (2009), whichincludes five common Facebook activities as partof their survey. Most studies of this type investi-gate only samples with specific demographiccharacteristics, and are therefore unable to per-form in-depth analysis of the issues being exam-ined, as they do not focus on investigating thebehavior of SNS users. The other type of question-naire research primarily focuses on understandinguser behavior. For instance, Kim et al. (2011) gath-ered SNS user behavior from past literature andthen used factor analysis to derive fivemotivationsfor it. Barker (2009) similarly used factor analysisto obtain six types of user motivation among olderadolescents. We found that the results of both Kimet al. (2011) and Barker (2009) include social net-working, entertainment, searching for informationand learning activities. Furthermore, a comparisonwith the results of studies that used clickstreamdata analysis revealed a number of similaritiesand differences; thus, these two research methodscan be used in a complementary fashion to helpresearchers more fully understand the behaviorsof SNS users.

Social Capital of Social Networking Sites

Social capital can be used to explain the overall orindividual structural relationships that exist insociety from a sociological perspective (Portes,1998). This structural relationship is a social sys-tem (Adler and Kwon, 2002). A person’s socialcapital refers to their relationships with others,which can serve as a source of benefits for thatperson (Coleman, 1988). In general, social capitalcan be divided into bonding and bridging capital(Katz and Aspden, 1997; Putnam, 2000). Bonding

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104 Tsung-Sheng Chang and Wei-Hung Hsiao

social capital refers to the cognitive similarity andhigher homogeneity of internal social groups,whereas bridging social capital is the socialrelations among more heterogeneous people, inwhich there are greater cognitive differences;thus, it is possible for individuals to form rela-tionships with greater levels of reciprocity andrecognition. We believe that social capital con-sists of social networks possessing value, and itis based on the individual social relationshipsthat make up a person’s social system. Forexample, in a social network, individuals canuse specific communication media to communi-cate with friends, and the relationships that existbetween friends are unique. Some friends arevaluable because they are amusing, others aremore helpful and other friends may have manyroles. An individual’s social system will includerelationships with different levels of trust andfamiliarity (Burt, 1992). In addition, significantemotional interchanges between individuals willalter their existing interpersonal relationship,causing changes to their social capital.An SNS is a complex network, and each indi-

vidual within it has his or her own set of socialrelationships, and if the structure of these rela-tionships can be interpreted, then this can helpus to understand each user (Piao et al., 2010).boyd and Ellison (2007) stated that SNSs permitindividuals to openly or semi-openly disclosetheir basic individual information to groups ofpeople with similar interests, allowing indivi-duals to meet and engage new friends online.Because of this, users’ SNS friends are not neces-sarily their friends met in real life, and their rela-tionships only exist within the virtual communityenvironment.Wang et al. (2012) stated that a virtual commu-

nity is a computer-mediated communication en-vironment and that if enough functional benefitsthat improve system interactivity are offered, thenit will be able to attract more members. Pasek et al.(2009) suggested that SNSs constitute virtual com-munities and people’s social behavior and charac-teristics are limited by the constraints of thewebsite system itself. As a consequence, users arenot necessarily able to express conventional socialbehaviors in a virtual environment in exactly thesame way as they would in a normal situation. In

effect, the virtual environment has its own charac-teristics, such as the fact that the veracity of certaininformation cannot be known with full certainty,which implies that there is a clear discrepancy be-tween how social capital is perceived in the realworld versus on SNSs. Huvila et al. (2010) studiedthe differences between social capital in real lifeand social capital in a virtual world (Second Life)and found that people with different levels of usehad different perceptions of social capital. How-ever, it remains to be determined whether thesame result will occur in the virtual environmentof an SNS. Donath and boyd (2004) suggested thatalthough SNSs serve as bridges enabling users toobtain and display their social capital, this doesnot mean that SNS users will always have goodsocial capital. This study therefore uses a surveyand employs statistical testing methods to deter-mine whether there are any significant differencesbetween social capital in real life and on SNSs.

RESEARCH DESIGN AND METHOD

Questionnaire Design

The questionnaire used in this study consists ofthree parts. The first part, which concerns theusers’ basic details, asked about their gender, age,tools used, number of friends in real life and onSNSs and amount of time spent on SNSs. In par-ticular, this study used the amount of SNS usageas a way of differentiating user groups. Wilsonet al. (2010) employedweeks as a unit for assessingamount of time spent using SNS, and the currentstudy also does this, with each usage option in-creasing in increments of 3 h (i.e. 0–3h is the lowestoption). Because the respondents consisted ofmembers of the general public in Taiwan, we con-sulted the research of Chou and Hsiao (2000), whofound in a study of college students in Taiwan that‘heavy users’ normally spend three times as muchtime online as ‘light users’. Because of this, wheninvestigating users’ SNS usage time in the ques-tionnaire, we felt it necessary to provide a timeoption that was three times greater than the mini-mum option. Consequently, we included fouroptions: 0–3, 3–6, 6–9h and over 9 h. From this,four user groups were formed according to the




amount of time spent on SNSs: members of groupA spent 0–3h per week using SNS, those in groupB spent 3–6 h, those in group C spent 6–9h and theheavy users, in group D, spent more than 9h perweek on SNSs.

We chiefly referenced the works of Benevenutoet al. (2009), Kim et al. (2010) and Schneider et al.(2009) when designing the user behavior ques-tions. The operational definitions of the mostfrequent types of user behavior are summarizedin Table 1.

The social capital measurement questions inthe third part of the questionnaire are based onthe measurement instruments in Huvila et al.(2010) and Onyx and Bullen (2000), and we donot consider the type of social capital (i.e. bridgingand bonding). All 13 questionswerewrittenwith adouble list design by selecting suitable variables toexamine the status of social capital on SNSs and inreal life (see Appendix). Each question used a five-point Likert scale, ranging from ‘strongly disagree’at 1 point to ‘strongly agree’ at 5 points.

Data Collection and Research Method

The questionnaires were gathered using an Inter-net survey method. We used online forums,bulletin board systems and SNSs as channels topublicize the questionnaire, and we encouragedrespondents to complete them at an online

questionnaire service provider (http://survey.youthwant.com.tw) or this study’s survey web-site. Questionnaires were collected from 13February to 31 July 2011, and the survey wasprimarily aimed at SNS users in Taiwan. A totalof 768 people filled out the questionnaire, and732 valid responses were obtained.

This study adopted descriptive statistics, multi-variate analysis of variance and the t-test as thestatistical methods. We used the statistical soft-ware package SPSS Statistics 17.0 (IBM, Armonk,NY, USA) to analyse the responses. The results ofthe reliability analysis for real-life and SNS socialcapital showed that the reliability values of bothwere roughly the same (Cronbach’s alpha=0.92).On the basis of the recommendation of Fornelland Larcker (1981) that the Cronbach’s alpha valueshould be at least 0.7, the internal consistency ofthe questionnaire was thus excellent. In addition,Hair et al. (1998) suggested that factor loadingsshould exceed 0.5.We calculated the factor loadingof the recovered sample, and this was greater than0.5 in all cases, indicating excellent convergentvalidity.

STATISTICAL RESULTS

This study classified the sample on the basis of theamount of SNS usage, with four groups, from lightto heavy, as noted earlier. The basic demographic

Table 1 Behavior of SNS users

Type of user behavior Description

Search Searching for interesting information or friends.Scrapbook or share personal information Sharing information or gossip, or responding to messages.Messages Engaging in online real-time communication and messaging with

others.Testimonial Giving testimonials or recommendations.Watch videos Watching videos online.Watch photos Watching photo online.Browse info posted by friend or communityinformation

Browsing information posted by friends or community members,for study, fun, and so on.

Browse info about the friends of friends orcommunity members

Browsing account profiles of friends of friends or communitymembers.

Use other extended or embeddedapplications

Use of other application programs or software incorporated onSNSs, such as Web games and multimedia editing programs.

Other activities, such as personal profileediting and idling

Other activities, including personal account editing or idling(i.e. away from keyboard) behavior.

SNS, social networking site.




http://survey.youthwant.com.tw

http://survey.youthwant.com.tw

distribution of the sample is as shown in Table 2.The total number of people in the sample was732, of which 328 belonged to group A, 156 togroups B and D, and 92 belonged to group C.Close to equal numbers of men and womencompleted the questionnaire, with only 3% moreof the latter. With regard to age, 96.2% wereyounger than 40years, and the largest numberwas in the 18- to 23-year age group (41%). Forthe equipment used to access SNS, the majoritystill used desktop computers (73.8%) and note-books (22.4%), with only 2.2% using smartphonesto do so. Furthermore, with regard to the numberof friends, 69.4% of respondents had more than30 SNS friends, and 39.9% had more than 100. Incontrast, no one had so many friends in real life,and only 19.7% of the respondents claimed to havemore than 30 friends in this context.

Table 3 shows the results of the statistical ana-lysis, and it can be seen that the different groupsexhibited somewhat different user behaviors. Interms of the overall results, the most commonform of SNS behavior was the use of other appli-cation programs. Approximately 20.5% of therespondents commonly used SNS to play gamesor used other embedded applications, and thispercentage was the highest in group D.

The paired-samples t-test was used to examinewhether any differences existed between SNSand real-life social capital for each group (seeTable 4). The results indicate that significant dif-ferences existed for groups A, B and C, as usersin these had different perceptions of social capitalin the two environments. The results of testingfor group D did not reach the level of significance(p> 0.05) and indicated that users in this group

Table 2 Profile of the respondents

Group A Group B Group C Group D n=732

0- to 3-h users 3- to 6-h users 6- to 9-h users >9-h users Total (%)

GenderMale 184 72 28 68 352 (48.1)Female 144 84 64 88 380 (51.9)

Age (years)<18 16 0 8 20 44 (6.0)18–23 140 68 40 52 300 (41.0)23–28 76 28 24 44 172 (23.5)28–33 60 40 16 28 144 (19.7)33–40 16 20 4 4 44 (6.0)>40 20 0 0 8 28 (3.8)

Equipment connected to SNSDesktop 272 116 56 96 540 (73.8)Laptop 44 28 36 56 164 (22.4)Smartphone 4 8 0 4 16 (2.2)Other mobile devices 4 0 0 0 4 (0.5)Other digital devices 4 4 0 0 8 (1.1)

SNS friends0 32 0 0 0 32 (4.4)1–10 56 12 0 20 88 (12.0)11–30 60 16 12 16 104 (14.2)30–100 92 60 24 40 216 (29.5)>100 88 68 56 80 292 (39.9)

Real-life friends0 24 0 4 12 40 (5.4)1–3 96 20 12 16 144 (19.7)4–10 112 68 20 24 224 (30.6)10–30 72 32 24 52 180 (24.6)>30 24 36 32 52 144 (19.7)

SNS, social networking site.




did not perceive a significant difference betweensocial capital on SNSs and in real life.

Multivariate of analysis was used to investigatesocial capital in the different groups, with theresult having a significant Wilks’s lambda (Wilk’slambda=0.827, p< 0.001). The statistical resultsshow that social capital on both SNS and in real lifereached levels of statistical significance (SNS:F=46.578, p< 0.001; real life: F=27.021, p< 0.001),indicating that at least one pair ofmean differencesreached the level of significance. In addition, theresults of Levene’s test for equality of variancesindicated that neither SNS nor real life socialcapital was significant, showing that the varianceswere not the same (SNS: F=4.888, p< 0.05; reallife: F=2.987, p< 0.05). Therefore, we also usedDunnett’s C method to perform post hoc testingand derived the differences between groups bycomparing the results, which are shown in Table 5.

DISCUSSION

Previous studies of user behavior on SNSs werepreliminary explorations that did not distinguishthe behaviors of different groups (e.g. Benevenutoet al., 2009; Valenzuela et al., 2009; Kim et al., 2011).In this study, we divided users into groups on thebasis of the time spent on SNSs to better under-stand their behavior, based on Tokunage andRains (2010), which noted that time spent using aparticular media can reveal details of the user’spsychological status, as well as how addicted theymay be to the media being examined. In thissection, we first discuss SNS user behavior andthen investigate users’ social capital, as explainedin more detail as follows.

Social Networking Sites User Behavior

We derived the respondents’ basic informationand user behavior by means of a descriptive stat-istical analysis of the sample. The results of thisanalysis indicate that users with different inten-sities of SNS usage exhibit different behaviors.However, users in each group spent similar per-centages of their usage time engaged in instantmessaging and other forms of communicationon SNSs. In addition, the same kinds of activities

Table 3 Comparisons of social networking sites’ user behavior between different user groups

Group A Group B Group C Group D

Type of user behavior0- to 3-husers (%)

3- to 6-husers (%)

6- to 9-husers (%)

>9-husers (%) Total (%)

Search 60 (18.3) 24 (15.4) 12 (13.0) 12 (7.7) 108 (14.8)Scrapbook or share personal information 16 (4.9) 8 (5.1) 8 (8.7) 12 (7.7) 44 (6.0)Messages 44 (13.4) 24 (15.4) 16 (17.4) 22 (14.1) 106 (14.5)Testimonial 60 (18.3) 8 (5.1) 12 (13.0) 25 (16.0) 105 (14.3)Watch videos 8 (2.4) 12 (7.7) 0 (0.0) 8 (5.1) 28 (3.8)Watch photos 28 (8.5) 20 (12.8) 8 (8.7) 16 (10.3) 72 (9.8)Browse info posted by friends or communityinformation

20 (6.1) 9 (5.8) 4 (4.4) 14 (9.0) 46 (6.3)

Browse info about the friends of friendsor community members

12 (3.7) 14 (9.0) 16 (17.4) 5 (3.2) 41 (5.6)

Use other extended or embedded applications(e.g. play Web game)

60 (18.3) 29 (18.6) 16 (17.4) 38 (24.4) 150 (20.5)

Other activities, such as personal profileediting and idling

20 (6.1) 8 (5.1) 0 (0.0) 4 (2.6) 32 (4.4)

Total (%) 328 (100) 156 (100) 92 (100) 156 (100) 732 (100.0)

Table 4 t-test of differences in perceived social capitalbetween social networking sites and real life

N t-value

Group A (0–3 h) 328 �8.830*Group B (3–6 h) 156 �7.384*Group C (6–9 h) 92 �4.749*Group D (>9 h) 156 �1.479

*p< 0.001.




accounted for low amounts of the users’ timein all groups, such as watching videos, postingor looking at photos and other activities,such as editing one’s personal information oridling, and do not represent the users’ mainreasons for using SNS. In addition, searchingbehavior accounted for a relatively large percent-age of time among users with low SNS usage,consistent with the finding of Emmanouilidesand Hammond (2000) that people who do notoften use websites engage in a relatively highamount of searching.The users in group D, who spent most time on

SNSs, spent a relatively large amount of their timeusing other applications or services (24.4%)provided by the SNSs, a much more time (16.0%)than they spent on giving testimonials, theirsecond most common behavior. Furthermore,these users spend a relatively low amount of timeon communication-related behaviors, which sup-ports the view that heavy SNS users do not neces-sarily spending much of their SNS time engagingin social networking activities. Moreover, thisgroup’s most common behavior, the use of appli-cations on the SNS, accounted for 20.5% of theusage time among the entire sample; thus, manySNS users engage in this activity. We thus arguethat the various application programs incorpo-rated in SNS are major factors that are attractingusers to such sites. In addition, the more a useruses an SNS, the more time he or she spends usingsuch applications. We thus recommend that SNSsthat wish to attract more long-term users shouldwork to provide application programs that users

will feel are interesting or useful. If SNS operatorsdo not have sufficient resources to invest in thedevelopment of new applications, they can insteadform alliances with software developers tojointly develop the market, as such cooperativemeasures can reduce the risks of uncertainty(Chakraborty, 2012) and may lead to mutuallybeneficial outcomes.

It can be seen from Table 3 that users in groupD spend a higher percentage of their time en-gaging in the two user behaviors of ‘Browse infoposted by friend or community information’ and‘Scrapbook or share personal information’ thanthe other groups. Because we do not considerwhether the users are browsing or sharing infor-mation content, this result implies that the morepeople use SNS, the more they regard SNS as amajor platform for sharing personal informationand acquiring knowledge. On the other hand,these activities do not account for large percen-tages of total use time within the sample as awhole, and very few users share information,accounting for only 6% of the entire sample.Looking from an academic perspective, Chiuet al. (2006) combined social capital theory andsocial cognition theory in an investigation of thebackground motivations for knowledge sharingin virtual communities. Their research suggestedthat individuals who are willing to share know-ledge hope to affirm their professionalism andearn the approval and attention of their collea-gues. In other words, perhaps not all SNS userswish to seek attention from their friends. How-ever, we infer from actual observations that the

Table 5 MANOVA analyses to test differences in perceived social capitals of different user groups with regard to SNS and reallife (Wilk’s lambda = 0.827, p< 0.001)

Sum of squares Df Mean square FPost hoc test

(Dunnett’s C method)

User groups Social capital on SNS 9390.158 3 3130.053 46.578* B>A; C>A;D>A; D>B;D>C

Social capital in real life 4730.240 3 1576.747 27.021* B>A; C>A;D>A

Error Social capital on SNS 48921.754 728 67.200Social capital in real life 42481.345 728 58.353

SNS, social networking site.A (0- to 3-h users); B (3- to 6-h users); C (6- to 9-h users); D (>9-h users).*p< 0.001.




information sharing mechanisms of existing SNSin the Taiwanese market lack the ability for usersto easily find historical information, and mostinformation on SNSs consists of gossip. This isconsistent with the argument of Yang and Lai(2011) that system and information quality willaffect users’ willingness to share knowledge. Itis recommended that future SNS should providebetter information sharing mechanisms, whichenable people to post and search for more valu-able information, as they may increase their will-ingness to do so.

Users’ Social Networking Sites and Real-LifeSocial Capital

The results of our study provide empirical sup-port for our proposition that there is a clear dif-ference in the social capital that exists in the realworld and on SNSs. Table 4 shows that, apartfrom group D, the heavy users, the other groupsall have significant differences in their percep-tions of social capital on SNSs and in real life,and all feel that the latter is more important thanthe former. This finding is consistent with theargument inDonath and boyd (2004),which statedthat SNS will not necessarily increase strong ties,such as relationships with existing close friends,and thus that people will still have better relation-ships with their original close friends than thosemet through SNS.

The results of the statistical analysis in Table 5reveal that there are significant differences inthe perceptions of social capital, both on SNSsand in real life, between users in group A, thelightest users, and those in other groups.However, this does not necessarily mean thatusers in group A lag behind those in othergroups in terms of their individual socialcapital structure or resources. We thus simplyinfer that users in group A do not have a higherperception of or regard for participation in socialnetworking activities, and the interpersonalcommunication that can occur there, than usersin other groups.

Although the results of this study show thatperceived social capital on SNSs differs depend-ing on the amount of time spent using such sites,

they do not reveal how an individual’s socialcapital can be changed by using SNS or explainthe possible reasons why users in group D havesimilar perceptions of their real-life and SNS-related social capital. Tong et al. (2008) and Wangand Wellman (2010) indicated that the numbersof friends a person has can express the extent ofhis or her basic social relationships. This studythus examines the number of network friendsthat exist in the different groups and whether thisis connected to the transformation of personalperceived social capital. The results are summar-ized in Figure 1. It can be seen that the proportionof SNS friends and real-world friends rises fromgroup A to group C. However, as users spendmore time on SNSs, there is a clear transform-ation in their perceived social capital. We con-clude that this may be because individual socialcapital undergoes a systematic shift (see Figure 2),

Time spent on SNSLow High

Group A Group B Group C Group D

Social capital differenceSocial capitalconsistency

Upper 100 SNS friend: 26%Upper 30 reallife friend: 7%

Upper 100 SNS friend: 43%Upper 30 real life friend: 23%



Note: a Social capital difference between the SNS and real life

Figure 1 Transformation of perceived social capital with thetime spent on a social networking site (SNS)

Increased use of time

Increased in the number of

SNS's friend

Social capitaldifference

Social capitalconsistency

Note: Social capital difference between the SNS and real life

Figure 2 Transformation of perceived social capital process:use time concept. SNS, social networking site




as follows. When people first start to use an SNS,they have few SNS friends and thus are likely tohave more friends in the real world. However,as a person’s number of SNS friends increases,he or she will spend more time using such sites.The results show a positive relationship betweenthe number of SNS friends and time spent onSNSs. As a person’s social relations graduallytransfer to an SNS context, the levels of socialcapital perceived in the virtual and real environ-ments will become increasingly similar, althoughthe number of SNS friends a person has will notnecessarily increase substantially. Moreover,Hsu et al. (2012) noted that higher levels of flowexperience (i.e. perceived enjoyment) will in-crease a user’s continuance intention with regardto system use. Because communicating withfriends and playing games are enjoyable experi-ences, we conclude that users in group D havehigher levels of flow experience on SNSs; thus,this is why they feel that there are no majordifferences between relationships with friend onSNSs and offline.

CONCLUSION

The rise of online social networks (SNSs) pro-vides a convenient way for people to make andmaintain friendships and thus engage in newforms of social behavior. It is anticipated thatthe results of this study should enable SNS opera-tors to better understand user behaviors andtheir perceptions of social capital. Because theresults of this work show that roughly one-fifthof users use other services provided by SNSs,and not just those for communicating withfriends, operators should work to develop func-tions that do not focus only on traditional socialnetworking activities, so as to increase theattractiveness of their sites and retain long-termusers. Furthermore, this study also examined dif-ferences in perceived social capital between userswith different levels of SNS usage and found thatthose who spend more time on SNSs do not seeany significant differences between their real-lifeand SNS social capital. In contrast, users whospend less time on SNSs do not place as muchimportance on the latter. We thus verified that

users with different amounts of SNS usage havedifferent user behaviors and perceptions of socialcapital and proposed a process to explain thetransformation of perceived social capital thatoccurs in this context. The results of this studymay provide a foundation for subsequentresearch on social capital and SNSs.

In the face of stiff competition in the SNSmarket, e-commerce firms must work to under-stand and meet users’ preferences. Hamperedby current technologies, today’s SNSs mostlyprovide only text communication and few emoti-cons, but future advances in communicationmethods will allow SNSs to offer other means ofcommunication, such as richer emoticons orvideo, and this will increase the level of per-ceived communication and thus enable users tocreate even better social relationships.

LIMITATIONS AND FUTURE RESEARCHRECOMMENDATIONS

This study has the following limitations, whichsuggest directions for future research. First, theresearch sample only included subjects fromTaiwan, and different results may be obtainedwith subjects from a different country or culture.However, because Taiwan has many similaritieswith China, the findings of this study should stillhave considerable value. Second, this study had a96.2% questionnaire recovery rate, with most ofthe respondents being younger than 40 yearsand only 3.8% older than this. As a result, thisstudy does not reflect the views and behaviorsof older users, and more research is thus neededto determine the SNS behaviors and perceivedsocial capital of this group. Third, this study usedthe amount of SNS use as a basis for differentiat-ing user groups, and different classificationcriteria may lead to different results. Finally, werecommend that other researchers perform amore in-depth investigation of SNS addictionand related behaviors. The current study exam-ines SNS use from the perspective of the positiveaspects, and an examination of the negative onesmay lead to a different understanding of SNSuser behavior.




REFERENCES

Adler PS, Kwon SW. 2002. Social capital: prospects fora new concept. Academy of Management Review 27(1):17–40.

AFP.com. 2010. More time spent on Facebook than Goo-gle: comScore. Available at: http://www.google.com/hostednews/afp/article/ALeqM5jEcNgf0f-aqtqRtA-M1iZy85dkXBA [Accessed on 15 September 2011].

Amiel T, Sargent SL. 2004. Individual differences inInternet usage motives. Computers in Human Behavior20(6): 711–726.

Barker V. 2009. Older adolescents’motivations for socialnetwork site use: the influence of gender, groupidentity, and collective self-esteem. Cyberpsychology &Behavior 12(2): 209–213.

Benevenuto F, Rodrigues T, Cha M, Almeida V. 2009.Characterizing user behavior in online socialnetworks. Proceedings of the 9th ACM SIGCOMMconference on Internet measurement conference,ACM: Association for Computing Machinery:New York.

boyd dm. 2008. Why youth (heart) social network sites:the role of networked publics in teenage social life.In Youth, identity, and digital media, Buckingham D(ed). MIT Press: Cambridge, MA; 119–142.

boyd dm, Ellison NB. 2007. Social network sites: defin-ition, history, and scholarship. Journal of Computer-Mediated Communication 13(1): 210–230.

Burke M, Marlow C, Lento T. 2010. Social network ac-tivity and social well-being. Proceedings of the 28thInternational Conference on Human Factors in Com-puting Systems. New York; 1909–1912.

Burke M, Kraut R, Marlow C. 2011. Social capital onFacebook: differentiating uses and users. Proceed-ings of the 2011 Annual Conference on Human Fac-tors in Computing Systems, ACM: Association forComputing Machinery: New York, 571–580.

Burt RS. 1992. Structural holes: the social structure of com-petition. Harvard University Press: Cambridge, MA.

Casale S, Fioravanti G. 2011. Psychosocial correlates ofinternet use among Italian students. InternationalJournal of Psychology 46(4): 288–298.

Chakraborty A. 2012. Recognizing uncertainty andlinked decisions in public participation: a newframework for collaborative urban planning. Sys-tems Research and Behavioral Science 29(2): 131–148.

Chiu CM, Hsu MH, Wang ETG. 2006. Understandingknowledge sharing in virtual communities: an inte-gration of social capital and social cognitive theories.Decision Support Systems 42(3): 1872–1888.

Choi JH, Scott JE. 2011. Social network sites and digitalword of mouth: a social capital perspective. AMCIS2011 Proceedings - All Submissions. Paper 400.Available at: http://aisel.aisnet.org/amcis2011_-submissions/400 [Accessed on 15 September 2011].

Choi SM, Kim Y, Sung Y, Sohn D. 2011. Bridgingor bonding? A cross-cultural study of social

relationships in social networking sites. Information,Communication and Society 14(1): 107–129.

ChouC, HsiaoMC. 2000. Internet addiction, usage, grati-fication, and pleasure experience: the Taiwan collegestudents’ case. Computers in Education 35(1): 65–80.

Coleman JS. 1988. Social capital in the creation ofhuman capital. The American Journal of Sociology 94(1):95–120.

Donath J, boyd dm. 2004. Public displays of connec-tion. BT Technology Journal 22(4): 71–82.

Ellison NB, Steinfield C, Lampe C. 2007. The benefits ofFacebook “friends:” social capital and collegestudents’ use of online social network sites. Journal ofComputer-Mediated Communication 12(4): 1143–1168.

Ellison NB, Steinfield C, Lampe C. 2011. Connectionstrategies: social capital implications of Facebook-enabled communication practices. New Media andSociety 13(6): 873–892.

Emmanouilides C, Hammond K. 2000. Internet usage:predictors of active users and frequency of use. Journalof Interactive Marketing 14(2): 17–32.

European Commission. 2011. Special Eurobarometer359. Available at: http://ec.europa.eu/information_society/digital-agenda/scoreboard/docs/pillar/studies/report_eb_743_eid_just_jrc_en_full_report_final.pdf [Accessed on 18 September 2011].

Fornell C, Larcker DF. 1981. Evaluating structural equa-tionmodelswith unobservable variables andmeasure-ment error. Journal of Marketing Research 18(1): 39–50.

Gilbert E, Karahalios K. 2009. Predicting tie strengthwith social media. Proceedings of the 27th Inter-national Conference on Human factors in computingsystems, ACM: Association for Computing Machin-ery: Boston.

Governatori G, Iannella R. 2011. A modelling andreasoning framework for social network policies.Enterprise Information Systems 5(1): 145–167.

Guo J, Gong Z. 2011. Measuring virtual wealth in virtualworlds. Information Technology and Management 12(2):121–135.

Hair JF, Anderson RE, Tatham RL, Black WC. 1998.Multivariate data analysis, 5th (edn.). Prentice Hall:Englewood Cliffs, NJ.

Hargittai E, Hsieh YP. 2010. Predictors and conse-quences of differentiated practices on social networksites. Information, Communication and Society 13(4):515–536.

Hong SJ, Thong JYL, Tam KY. 2006. Understandingcontinued information technology usage behavior: acomparison of three models in the context of mobileinternet. Decision Support Systems 42(3): 1819–1834.

Hsu CL, Chang KC, Chen MC. 2012. Flow experienceand Internet shopping behavior: investigating themoderating effect of consumer characteristics.Systems Research and Behavioral Science 29(3): 317–332.

Huvila I, Holmberg K, Ek S, Widén-Wulff G. 2010.Social capital in Second Life. Online InformationReview 34(2): 295–316.




http://www.google.com/hostednews/afp/article/ALeqM5jEcNgf0f-aqtqRtAM1iZy85dkXBA



http://ec.europa.eu/information_society/digital-agenda/scoreboard/docs/pillar/studies/report_eb_743_eid_just_jrc_en_full_report_final.pdf




Ji YG, Hwangbo H, Yi JS, Rau PLP, Fang X, Ling C.2010. The influence of cultural differences on theuse of social network services and the formation ofsocial capital. International Journal of Human ComputerInteraction 26(11-12): 1100–1121.

Katz J, Aspden P. 1997. A nation of strangers?. Commu-nications of the ACM 40(12): 81–86.

Kim W, Jeong OR, Lee SW. 2010. On social Web sites.Information Systems 35(2): 215–236.

Kim Y, Sohn D, Choi SM. 2011. Cultural differencein motivations for using social network sites:a comparative study of American and Koreancollege students. Computers in Human Behavior 27(1):365–372.

Lin N. 1999. Building a network theory of social capital.Connections 22(1): 28–51.

Lu HP, Lin JCC. 2002. Predicting customer behavior inthe market-space: a study of Rayport and Sviokla’sframework. Information Management 40(1): 1–10.

Lykourentzou I, Dagka F, Papadaki K, Lepouras G,Vassilakis C. 2012. Wikis in enterprise settings: asurvey. Enterprise Information Systems 6(1): 1–53.

Madden M, Zickuhr K. 2011. 65% of online adults usesocial networking sites. Pew Internet & American LifeProject. Pew Research Center: Washington, DC.

Mathwick C, Wiertz C, de Ruyter K. 2008. Socialcapital production in a virtual P3 community. Journalof Consumer Research 34(6): 832–849.

Miller R, Parsons K, Lifer D. 2010. Students and socialnetworking sites: the posting paradox. Behaviour andInformation Technology 29(4): 377–382.

Nahapiet J, Ghoshal S. 1998. Social capital, intellectualcapital, and the organizational advantage. Academyof Management Review 23(2): 242–266.

Onyx J, Bullen P. 2000. Measuring social capital in fivecommunities. The Journal of Applied Behavioral Science36(1): 23–42.

Pasek J, More E, Romer D. 2009. Realizing the socialinternet? Online social networking meets offlinesocial capital. Journal of Information Technology andPolitics 6(3-4): 197–215.

Piao C, Han X, Wu H. 2010. Research on e-commercetransaction networks using multi-agent modellingand open application programming interface. Enter-prise Information Systems 4(3): 329–353.

van den Poel D, Buckinx W. 2005. Predicting online-purchasing behaviour. European Journal of Oper-ational Research 166(2): 557–575.

Portes P. 1998. Social capital: its origins and applica-tions in modern sociology. Annual Review of Sociology24(1): 1–24.

Putnam RD. 2000. Bowling Alone: The Collapse andRevival of American Community. Simon and Schuster:New York.

Riva G, Teruzzi T, Anolli L. 2003. The use of the Internetin psychological research: comparison of onlineand offline questionnaires. Cyberpsychology & Behavior6(1): 73–80.

Schneider F, Feldmann A, Krishnamurthy B, WillingerW. 2009. Understanding online social network usagefrom a network perspective. Proceedings of theIMC ’09 Proceedings of the 9th ACM SIGCOMMconference on Internet measurement conference,ACM: Association for Computing Machinery: NewYork.

Steinfield C, Ellison NB, Lampe C. 2008. Social capital,self-esteem, and use of online social network sites: alongitudinal analysis. Journal of Applied DevelopmentalPsychology 29(6): 434–445.

Tokunage RS, Rains SA. 2010. An evaluation of twocharacterizations of the relationships between prob-lematic Internet use, time spent using the Internet,and psychosocial problems. Human CommunicationResearch 36(4): 512–545.

Tong ST, van der Heide B, Langwell L, Walther JB.2008. Too much of a good thing? The relationshipbetween number of friends and interpersonalimpressions on Facebook. Journal of Computer-Mediated Communication 13(3): 531–549.

Valenzuela S, Park N, Kee KF. 2009. Is there socialcapital in a social network site? Facebook use andcollege students’ life satisfaction, trust, and partici-pation. Journal of Computer-Mediated Communication14(4): 875–901.

Wang H, Wellman B. 2010. Social connectivity inAmerica: changes in adult friendship network sizefrom 2002 to 2007. American Behavioral Scientist 53(8):1148–1169.

Wang EST, Chen LSL, Tsai BK. 2012. Investigatingmember commitment to virtual communities usingan integrated perspective. Internet research 22(2):199–210.

Wellman B, Haase AQ, Witte J, Hampton K. 2001. Doesthe Internet increase, decrease, or supplement socialcapital? Social networks, participation, and commu-nity commitment. American Behavioral Scientist 45(3):436–455.

White L. 2002. Connection matters: exploring theimplications of social capital and social networksfor social policy. Systems Research and BehavioralScience 19(3): 255–269.

Wilson K, Fornasier S, White KM. 2010. Psychologicalpredictors of young adults’ use of social networkingsites. Cyberpsychology, Behavior and Social Networking13(2): 173–177.

Yang H-L, Lai C-Y. 2011. Understanding knowledge-sharing behaviour in Wikipedia. Behaviour and Infor-mation Technology 30(1): 131–142.




APPENDIX

ITEMS OF SOCIAL CAPITAL QUESTIONNAIRE

Social capital on social networking sites.

1. I feel that social activities on a social networking sitehave value.2. I believe that helping other people on a socialnetworking site is the same as helping myself.3. I have served as a volunteer helping other people ona social networking site.4. Most people on social networking sites aretrustworthy.5. When you need help, you can get help from yourfriends on social networking sites.6. I have participated in a group activity held by asocial networking site during the past 6months.7. I am an active member of a social networking site.8. Yesterday I chatted with many people on a socialnetworking site.9. I frequently recommend to my social networking sitefriends that they join me when I take part in an onlineactivity.10. I have given a testimonial on a social networkingsite for a friend within the past 6months.11. The multicultural interchanges they allow make mefeel that social networking sites are great.12. If I do not see eye to eye with someone on a socialnetworking site, I will still freely express my opinion.

13. I would be very willing to obtain mediation if Ihad a conflict with a friend on a social networkingsite.

Social capital in real life.

1. I feel that social activities in real life have value.2. I believe that helping other people in real life is thesame as helping myself.3. I have served as a volunteer helping other people inreal life.4. Most people in real life are trustworthy.5. I can obtain help from a friend in real life if I needassistance.6. I have participated in a real-life group activityduring the past 6months.7. I am a cheerful member of social groups.8. Yesterday I chatted face to face with many people.9. When I take part in an activity, I frequently ask myfriends to join me.10. I commended my friend in real life within the past6months.11. In real life, the multicultural interchange makes mefeel great.12. If I do not see eye to eye with someone in real life, Iwill still freely express my opinion.13. I would be very willing to obtain mediation if I hada face-to-face conflict with a friend.




Documents

Time Spent on Social Networking Sites: Understanding User Behavior and Social Capital