Personal networks on social network sites (SNS) – Context and personality influences zur Erlangung des akademischen Grades eines Doktors der Wirtschaftswissenschaften (Dr. rer. pol.) von der Fakultat¨ fur¨ Wirtschaftswissenschaften der Universitat¨ Fridericiana zu Karlsruhe genehmigte DISSERTATION von Dipl.-Psych. Cora Schaefer Tag der mundlichen¨ Prufung:¨ 29.07.2008 Referent: Prof. Dr. Andreas Geyer-Schulz Koreferent: Prof. Dr. Siegfried Berninghaus Karlsruhe, 2008 0 Contents 1 INTRODUCTION 1 1.1 MOTIVATION ................................ 1 1.2 RESEARCH QUESTIONS .......................... 3 1.3 OVERVIEW AND STRUCTURE ....................... 4 1.4 RELATED PUBLICATIONS ......................... 5 2 FOUNDATIONS 7 2.1 SOCIAL NETWORK ANALYSIS ....................... 7 2.1.1 SNA as paradigm and toolkit . 9 2.1.2 Discriminating actors: Centrality . 10 2.1.3 Discriminating ties: The strength of ties . 11 2.1.4 Summary . 12 2.2 SOCIAL NETWORK SITES .......................... 13 2.2.1 Description . 13 2.2.2 Features of SNSs . 18 2.2.3 Clarification on terminology . 21 2.2.4 Literature overview . 21 2.2.5 Summary . 23 2.3 THE RELATIONAL DATA ON SNSS ..................... 23 2.4 THE RESEARCH MODEL .......................... 26 2.5 SUMMARY ................................. 27 3 INFLUENCE OF THE ENVIRONMENT 29 3.1 CONCEPTUAL ANALYSIS .......................... 30 3.1.1 Influences on the composition of the user population . 31 3.1.1.1 The technical framework . 31 3.1.1.2 The regulatory framework . 31 3.1.1.3 The mission statement . 32 3.1.1.4 The culture ........................ 33 3.1.2 Factors influencing the hyperlinks between profiles . 33 3.1.2.1 The technical framework . 34 3.1.2.2 The mission statement . 35 3.1.2.3 The culture ........................ 35 3.1.3 Discussion of the meaning inherent in a hyperlink between profiles 36 3.1.4 Summary . 38 3.2 EMPIRICAL STUDIES ............................ 38 i ii CONTENTS 3.2.1 Field study on the effects of a fake hub in a social network . 38 3.2.1.1 Discussion fora as social networks . 39 3.2.1.2 Hypotheses ........................ 40 3.2.1.3 The investigated discussion forum and data . 41 3.2.1.4 Analysis of degree centrality . 43 3.2.1.5 Analysis of the eigensystems . 45 3.2.1.6 Discussion ........................ 48 3.2.1.7 Summary ......................... 49 3.2.2 Field study on the effect of linking costs on the number of realized links . 49 3.2.2.1 The effect of linking costs . 49 3.2.2.2 The investigated social networks sites . 50 3.2.2.3 Results .......................... 51 3.2.2.4 Discussion ........................ 51 3.2.2.5 Summary ......................... 52 3.2.3 Survey study on the meaning of SNS data . 52 3.2.3.1 SNSs as form of computer-mediated communication . 52 3.2.3.2 Research questions .................... 54 3.2.3.3 The studied SNS ..................... 56 3.2.3.4 Questionnaire and sample description . 57 3.2.3.5 Results .......................... 61 3.2.3.6 Discussion ........................ 65 3.3 SUMMARY ................................. 68 4 INFLUENCE OF INDIVIDUAL ATTRIBUTES 71 4.1 INDIVIDUAL ATTRIBUTES ......................... 72 4.1.1 Motivation . 73 4.1.2 Personality . 74 4.1.3 Measurement of individual attributes . 78 4.2 HYPOTHESES AND RELATED WORK .................... 79 4.2.1 Personal network size . 80 4.2.2 Establishing new ties . 82 4.3 THE QUESTIONNAIRE ........................... 84 4.3.1 Motivation . 85 4.3.2 Personality . 86 4.4 RESULTS .................................. 89 4.4.1 Personal network size . 90 4.4.1.1 Motivation ........................ 90 4.4.1.2 Personality ........................ 91 4.4.2 Establishing new ties . 96 4.4.2.1 Motivation ........................ 96 4.4.2.2 Personality ........................ 96 4.5 DISCUSSION ................................ 97 4.6 SUMMARY .................................101 CONTENTS iii 5 CONCLUSION 103 5.1 SUMMARY OF CONTRIBUTIONS AND REVIEW OF WORK . 103 5.2 FUTURE WORK ...............................107 Appendix 108 A The complete questionnaire 109 B Statistics of the survey study 123 B.1 TESTS OF DIFFERENCES I . 123 B.2 THE DIFFERENCE IN THE DROP-OUT RATE DUE TO THE ORDERING OF THE SURVEY PARTS IN THE QUESTIONNAIRE STUDY . 126 C Statistics on individual attributes 127 C.1 FORMULAS OF EMPLOYED STATISTICS . 127 C.2 TEST OF DIFFERENCES II . 127 C.3 FACTOR ANALYSIS OF THE INDIVIDUAL VARIABLES . 130 C.4 CORRELATIONS WITH SOCIODEMOGRAPHIC VARIABLES . 133 C.5 PARTIAL KENDALL-τ STATISTICS . 135 List of figures 137 List of tables 138 Bibliography 141 iv CONTENTS Chapter 1 Introduction Society and markets move online: A considerable and ever-growing part of life and of economic activity takes place in the Internet today. People seek information and enter- tainment online and increasingly, also social interaction meeting and communicating with familiar persons as well as with strangers. A side effect of peoples’ actions in the Internet is the digital trail of data left behind which is easily collected. With the emergence of interactive and personalized applications which invite as well as build on peoples’ contri- butions the data trail is enriched by the data of personal profiles. Furthermore, the profiles facilitate histories of behavior as well as of interactions with other users given that the application permits social encounter. Hence, it is estimated that a person born these days leaves a digital trail of 10 terabytes of data throughout his life (Smith, 2006). These data may offer valuable insights on manifold issues because the availability of data of millions of persons is unprecedented. A recent instance of an interactive and personalized Internet application are social network sites which promote primarily the possibility to exhibit the social connections of their participants. 1.1 Motivation Currently, social network sites (SNSs) receive great interest from all sides. They attract millions of users1 who also frequently spend time in the SNS: of teenagers, almost half visit it daily (Lenhart and Madden, 2007a) while college students use it daily and spend on average 20 minutes per day there (Ellison et al., 2007). Adults visit SNSs less often, but regularly, e.g. once a month (Faber, 2007). Thus, SNSs are considered mainstream nowadays (Beer, 2008). Furthermore, SNSs receive continued media coverage and start to rouse academic interest as well (e.g. boyd and Ellison, 2007). Both, the media and research articles raise sociological as well as economical questions. For instance, it is asked how SNSs change our lives and how they can be employed for marketing purposes. In line with this, SNSs attract investors’ interest. This is evidenced by recent acquisitions of SNS companies (Stroud, 2008) or of stakes thereof (Kuri, 2007). Moreover, SNS firms obtain high valuations, e.g. Facebook was recently valued at 15 billion $ (Kuri, 2007). 1E.g. Facebook has 70 million users (Facebook, 2008), Friendster 65 million (Friendster, 2008), LinkedIn 20 million (LinkedIn Corporation, 2008), MySpace 110 million (Swartz, 2008), and Xing 3 mil- lion (Heise, 2007) 1 2 CHAPTER 1. INTRODUCTION The business interest can be explained by two facts. First, SNSs represent economies of scale because the service, once running, can handle a certain amount of users and within this range, the operating costs per user decrease the more user the SNS has. Sec- ond and more important, they contain vast amounts of personal information of their users. This allows to infer information about users which they have not revealed themselves us- ing the information reported by their contacts (He et al., 2006; MacKinnon and Warren, 2006). Consequently, possible applications for marketing purposes have been consid- ered (Clemons et al., 2007; Stroud, 2008). Moreover, besides the personal information of users, also relational information about their connections to others, and again their connections, and so on, is available on SNSs. This further increases their attractivity for investors because SNSs can thus be a valuable source concerning information of personal relationships. Personal relationships play a special role in marketing because the information and recommendations of other persons have consistently been shown to exert a much greater impact on persons’ buying decisions than various forms of advertisement (Katz and Lazarsfeld, 1962; Dichter, 1966; Johnson Brown and Reingen, 1987). Thus, personal relationships shape consumer’s decisions, e.g. persons of the same social circle have been shown to use the same brands (Reingen et al., 1984). It has been recognized early that the influence of personal recommendations rests on the very fact that the recommending person has no material interest of her own in the decision of the other (Dichter, 1966). Rather, persons recommend goods or services to others out of self-related motivations, e.g. feeling or appearing knowledgeable, or out of other-related motivations, e.g. intend- ing to be helpful. Due to the success of personal recommendations, firms have tried to approximate these communications in their marketing campaigns and newer approaches even attempt to consciously engineer such seemingly private communications by hiring agents for this task (Carl, 2006). Consequently, it has been concluded that “much of marketing is relational” (Iacobucci, 1996, p. 15). These informal conversations about products and services between friends or acquain- tances, such as neighbors, have been termed word of mouth and they shape persons in their attitudes and behavior towards goods (Johnson Brown and Reingen, 1987). Regard- ing the Internet, first findings show that in online communities, the website itself on which the word of mouth took place influences the evaluation of the credibility of the received information next to the individual contributor (Brown et al., 2007). The data of SNSs are relevant for marketing purposes in two respects, namely as a po- tential channel for word of mouth processes and as a source of data for the identification of optimal candidates to start a campaign of word of mouth marketing. For this, highly connected persons who are able to reach many third persons and thus increase the effec- tivity of the marketing efforts should be targeted (Krackhardt, 1996).