An Economic Analysis of Peer Disclosure in Online Social Communities
Zike Cao, Kai-Lung Hui, Xu Hong
Information Systems Research
- 주제온라인 개인정보 보호 · 소셜미디어
- 방법
- 현상
We study a novel privacy concern, i.e., peer disclosure of sensitive personal information in online social communities. We model peer disclosure as the imposition of a negative externality on other people. Our model encompasses the benefits of posting information, positive externalities in the form of recognition and entertainment benefits due to others’ sharing of information, and heterogeneous privacy preferences. We find that regulation of peer disclosure is necessary. We consider two candidate regulations, i.e., nudging and quotas. Nudging reduces user participation and privacy harm and sometimes improves social welfare. By contrast, imposing a quota often improves user participation, privacy protection, and social welfare. Adding a nudge on top of a quota does not bring additional benefits. We show that any regulation that uniformly controls the disclosure of sensitive and nonsensitive information will not serve the triple objectives of reducing privacy harm, increasing social welfare, and increasing information contribution. We derive a necessary condition for solutions that can fulfill these three objectives. We also compare the incentives of the platform owner and social planner and draw related managerial and policy implications. The online appendix is available at https://doi.org/10.1287/isre.2017.0744 .
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- 저널Information Systems Research · 29(3) · 546–566
- 토픽Privacy, Security, and Data Protection · Sociology and Political Science
- DOI10.1287/isre.2017.0744
- 저자Zike Cao, Kai-Lung Hui, Xu Hong