An Economic Analysis of Peer Disclosure in Online Social Communities

• Published in: Information systems research Vol. 29; no. 3; pp. 546 - 566
• Main Authors: Cao, Zike, Hui, Kai-Lung, Xu, Hong
• Format: Journal Article
• Language: English
• Published: Linthicum INFORMS 01-09-2018; Institute for Operations Research and the Management Sciences
• Subjects: Analysis; Community; Data integrity; Disclosure; Economic analysis; Economic development; Iran; Laws, regulations and rules; New York; nudging; online social communities; peer disclosure; Personal information; Privacy; Privacy, Right of; quota; regulation; Social networks; Iran; New York
• ISSN: 1047-7047; 1526-5536
• DOI: 10.1287/isre.2017.0744

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
.