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Published November 2013 | public
Journal Article

Information-sharing in social networks

Abstract

We present a new model for reasoning about the way information is shared among friends in a social network and the resulting ways in which the social network fragments. Our model formalizes the intuition that revealing personal information in social settings involves a trade-off between the benefits of sharing information with friends, and the risks that additional gossiping will propagate it to someone with whom one is not on friendly terms but who is within oneʼs community. We study the behavior of rational agents in such a situation, and we characterize the existence and computability of stable information-sharing configurations, in which agents do not have an incentive to change the set of partners with whom they share information. We analyze the implications of these stable configurations for social welfare and the resulting fragmentation of the social network.

Additional Information

© 2013 Elsevier Inc. Received 25 May 2012, Available online 23 October 2013. The authors gratefully acknowledge the useful comments and suggestions of the reviewers, the advisory editor, Leeat Yariv, Emerson Melo, and seminar participants at Cornell University, Hebrew University, Penn State, the Technion, and Tel Aviv University. This work has been supported in part by NSF grants CCF-0325453, BCS-0537606, IIS-0705774, IIS-0910664, CCF-0910940, IS-1016099, a Simons Investigator Award, an ARO MURI grant, a Google Research Grant, a Yahoo! Research Alliance Grant, and the John D. and Catherine T. MacArthur Foundation. Work completed in part while the author was a postdoctoral associate at Cornell University. This work has been supported in part by an NSF Computing Innovation Fellowship (NSF Award CCF-0937060), an NSF Mathematical Sciences Postdoctoral Fellowship (NSF Award DMS-1004416), NSF grants CCF-0910940 and CNS-1254169, the Charles Lee Powell Foundation, and a Microsoft Faculty Fellowship.

Additional details

Created:
August 22, 2023
Modified:
October 17, 2023