Social networking sites (SNSs) have emerged as parallel societies, providing individuals with a platform to interact with peers and construct their desired self-identities. However, maintaining a positive image and safeguarding oneself from social judgment often necessitate self-censorship in self-identity expression. Drawing upon the privacy calculus theory, this study investigates how SNS users engage in a rational cost–benefit analysis between peer privacy concerns and self-presentation when deciding whether to actively or passively use SNSs. Findings from a variance-based analysis—partial least squares structural equation modeling (PLS-SEM)—to a sample of 394 Facebook users revealed that active use was primarily driven by perceived benefits, while passive use was triggered by perceived privacy costs. However, employing a case-based analysis—fuzzy-set qualitative comparative analysis (fsQCA), the present study uncovered that while some SNS users do not conform to the privacy calculus, many others do, thereby confirming the proposed dual privacy calculus model for SNS use. These findings resolve the contradictory findings from previous research on the privacy calculus model. This study extends the literature on the privacy calculus theory by developing a dual peer privacy calculus model to understand SNS users’ passive and active uses and validate the significance of peer privacy concerns on these behavioral patterns. This study underscores critical factors influencing SNS usage patterns, empowering platform developers to provide users with effective tools to combat privacy violations by peers, thereby promoting increased active engagement.

中文翻译：

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同伴隐私问题如何影响社交网站的主动和被动使用：双重同伴隐私演算模型

社交网站 (SNS) 已成为平行社会，为个人提供了与同伴互动并构建其所需的自我认同的平台。然而，保持积极的形象并保护自己免受社会评判往往需要在自我认同表达中进行自我审查。本研究借鉴隐私演算理论，研究了社交网络服务用户在决定主动还是被动使用社交网络服务时，如何在同伴隐私关注和自我展示之间进行理性的成本效益分析。对 394 名 Facebook 用户进行基于方差的分析（偏最小二乘结构方程模型 (PLS-SEM)）的结果表明，主动使用主要是由感知到的好处驱动的，而被动使用则是由感知到的隐私成本引发的。然而，采用基于案例的分析——模糊集定性比较分析（fsQCA），本研究发现，虽然一些 SNS 用户不符合隐私演算，但许多其他用户却遵守，从而证实了所提出的 SNS 双重隐私演算模型使用。这些发现解决了之前隐私演算模型研究中相互矛盾的发现。本研究通过开发双重对等隐私演算模型来扩展隐私演算理论的文献，以了解 SNS 用户的被动和主动使用，并验证对等隐私问题对这些行为模式的重要性。这项研究强调了影响 SNS 使用模式的关键因素，使平台开发人员能够为用户提供有效的工具来打击同行侵犯隐私的行为，从而促进积极参与。