Determining a Discrete Set of Site-Constrained Privacy Options for Users in Social Networks through Stackelberg Games

Meeting Details

For more information about this meeting, contact Carina Curto, Timothy Reluga.

Speaker: Sarah Rajtmajer, Penn State Math

Abstract: The privacy policies of an online social network play an important role in determining user involvement and satisfaction, and in turn site profit and success. In this talk, we present a game theoretic framework to model the relationship between the set of privacy options offered by a social network site and the sharing decisions of its users within these constraints. We model the site and the users in this scenario as the leader and followers, respectively, in a Stackelberg game. We formally establish the conditions under which this game reaches a Nash equilibrium in pure strategies and provide an approximation algorithm for the site to determine a discrete set of privacy options to maximize payoff. We validate hypotheses in our model on data collected from a mock-social network of users' privacy preferences both within and outside the context of peer influence, and demonstrate that the qualitative assumptions of our model are well-founded.

---

Room Reservation Information

Room Number: 106 McAllister

Date: 10/27/2015

Time: 1:30pm - 2:20pm