Development and Analyses of Privacy Management Models in Online Social Networks Based on Communication Privacy Management Theory.

ix 1. PROBLEM DEFINITION . 1 2. LITERATURE REVIEW . 10 3. MODELING . 29 4. VALIDATION AND INTERPRETATION . 47 5. DISCUSSION . 75 6. CONCLUSION . 81 REFERENCES . 85 APPENDICES . 93 Background . 94 Cultural orientation . 94 PART I: Behavior ‐ offline . 94 PART II: Behaviors – Social networking Site . 97 vi Gender orientation . 99 Part1 ‐ offline . 99 Part2 – Social Networking Site . 100 Perceived Risk / Benefit ratio of disclosure . 101 Communication apprehension . 106 Interpersonal Communication Motive . 107 Self‐disclosure . 108 Behavior of privacy management . 110 PART1 – Permeability: Control of information flow . 110 Part 2 ‐ Boundary ownership: assign different access privilege to different people . 112 Part 3 – Boundary linkage: selectively reveal private information . 113 Demography . 114 VITA . 115 vii LIST OF TABLES Table 1 Existing studies using top‐down approach . 17 Table 2 Existing studies using bottom‐up approach . 18 Table 3 Terms and definitions used in SEM . 46 Table 4 Criteria used for determining model fit . 48 Table 5 Reliability, convergent validity, and discriminant validity for measurement model of TPB constructs . 50 Table 6 Three factor solution as a result of EFA on motivational criteria . 60 Table 7 Two factor solution as a result of EFA on Unwillingness to communicate . 65 Table 8 Two factor solution as a result of EFA on Self‐disclosure . 67 Table 9 Overview of hypotheses testing . 74 viii LIST OF FIGURES Figure 1 Overview of privacy rule development in CPM . 26 Figure 2 The theory of planned behavior as illustrated in Fishbein and Ajzen (2010) . 27 Figure 3 Core research constructs from TPB . 28 Figure 4 Generic procedure of SEM (R. B. Kline, 2005) . 30 Figure 5 A combined model of CPM theory and TPB represented in a model . 32 Figure 6 Race distribution of the dataset . 33 Figure 7 Degree of Education in the dataset . 33 Figure 8 Age distribution in the dataset . 34 Figure 9 Risk / benefit ratio questionnaire construction . 42 Figure 10 Criteria used for determining reliability, convergent validity, and discriminant validity . 48 Figure 11 A structural model of behavioral constructs from TPB . 51 Figure 12 A structural model of cultural criteria . 55 Figure 13 A structural model of gender criteria . 58 Figure 14 A structural model of motivational criteria . 63 Figure 15 A structural model of context criteria . 70 Figure 16 A structural model of risk / benefit ratio criteria . 73 Figure 17 Word cloud based on what users would want to manage boundary permeability in online social networks . 80 ix ABSTRACT Development and analysis of privacy management models in online social networks based on communication privacy management theory Advisor: Il-Yeol Song, Ph.D. Online social networks (OSNs), while serving as an emerging means of communication, promote various issues of privacy. Users of OSNs encounter diverse occasions that lead to invasion of their privacy, e.g., published conversation, public revelation of their personally identifiable information, and open boundary of distinct social groups within their social network. However, social networking websites seldom support user needs in privacy while users expect experience of privacy management as they do in real life. There is a fundamental discrepancy between natural way of user's privacy experience and design of usable privacy in OSNs. In order to understand how people make decisions of their privacy management in OSNs, examination of conceptual structure is needed. The goals of this dissertation are identifying research constructs and developing models of user’s privacy management behavior, and testing the constructs and the models based on meaningful hypotheses. Throughout analyses, we identified research constructs based on Communication Privacy Management theory, developed a set of causal models showing influence of user traits and perceptions on their behavior of privacy management in OSNs, and tested a set of hypotheses using Structural Equation Modeling. The results indicate that users with collectivistic trait are less likely to manage privacy in OSNs while male users and female users do not show difference. Users are less likely to manage privacy when their motivation of disclosure is self-presentation while they are more likely to manage privacy when it is for communication. In addition, users are more likely to manage privacy when the context of privacy management relates to higher unwillingness x to communicate and more active self-disclosure. Our models show that influence to privacy is multi-dimensional and thus, patterns of user behavior in regards to privacy management vary. Established models are significant in that they can be used in various ways; first, they provide users with a basis for educational material of privacy management in OSNs; second, designers of user experience can make reference to the models while designing usable privacy for their services, and; finally, they provide researchers with foundational findings for further research in privacy management in OSNs.