An Extended Privacy Calculus Model for SNSs: Analyzing Self-Disclosure and Self-Withdrawal in a Representative US Sample

被引:262
作者
Dienlin, Tobias [1 ]
Metzger, Miriam J. [2 ]
机构
[1] Univ Hohenheim, Dept Media Psychol 540 F, D-70599 Stuttgart, Germany
[2] Univ Calif Santa Barbara, Dept Commun, Ellison Hall, Santa Barbara, CA 93106 USA
关键词
Privacy Calculus; Privacy Paradox; Self-Efficacy; Facebook; Structural Equation Modeling; Representative Sample; SOCIAL NETWORKING SITES; INFORMATION DISCLOSURE; ANTECEDENTS; USERS;
D O I
10.1111/jcc4.12163
中图分类号
G2 [信息与知识传播];
学科分类号
05 ; 0503 ;
摘要
The privacy calculus established that online self-disclosures are based on a cost-benefit tradeoff. For the context of SNSs, however, the privacy calculus still needs further support as most studies consist of small student samples and analyze self-disclosure only, excluding self-withdrawal (e.g., the deletion of posts), which is essential in SNS contexts. Thus, this study used a U.S. representative sample to test the privacy calculus' generalizability and extend its theoretical framework by including both self-withdrawal behaviors and privacy self-efficacy. Results confirmed the extended privacy calculus model. Moreover, both privacy concerns and privacy self-efficacy positively predicted use of self-withdrawal. With regard to predicting self-disclosure in SNSs, benefits outweighed privacy concerns; regarding self-withdrawal, privacy concerns outweighed both privacy self-efficacy and benefits.
引用
收藏
页码:368 / 383
页数:16
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