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

Dienlin, Tobias ; Metzger, Miriam J.

Journal of computer-mediated communication, 2016-09, Vol.21 (5), p.368-383 [Periódico revisado por pares]

Oxford, UK: Blackwell Publishing Ltd

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  • Título:
    An Extended Privacy Calculus Model for SNSs: Analyzing Self-Disclosure and Self-Withdrawal in a Representative U.S. Sample
  • Autor: Dienlin, Tobias ; Metzger, Miriam J.
  • Assuntos: Calculus ; Deletion ; Facebook ; Mathematical analysis ; Mathematical models ; Privacy ; Privacy Calculus ; Privacy Paradox ; Representative Sample ; Self-Efficacy ; Structural Equation Modeling ; Students
  • É parte de: Journal of computer-mediated communication, 2016-09, Vol.21 (5), p.368-383
  • Notas: ArticleID:JCC412163
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  • Descrição: 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.
  • Editor: Oxford, UK: Blackwell Publishing Ltd
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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