TY - JOUR
T1 - An Extended Ultimatum Game for Multi-Party Access Control in Social Networks
AU - Squicciarini, Anna
AU - Rajtmajer, Sarah
AU - Gao, Yang
AU - Semonsen, Justin
AU - Belmonte, Andrew
AU - Agarwal, Pratik
N1 - Publisher Copyright:
© 2022 Association for Computing Machinery.
PY - 2022/9/28
Y1 - 2022/9/28
N2 - In this article, we aim to answer an important set of questions about the potential longitudinal effects of repeated sharing and privacy settings decisions over jointly managed content among users in a social network.We model user interactions through a repeated game in a network graph. We present a variation of the one-shot Ultimatum Game, wherein individuals interact with peers to make a decision on a piece of shared content. The outcome of this game is either success or failure, wherein success implies that a satisfactory decision for all parties is made and failure instead implies that the parties could not reach an agreement. Our proposed game is grounded in empirical data about individual decisions in repeated pairwise negotiations about jointly managed content in a social network. We consider both a "continuous"privacy model as well the "discrete"case of a model wherein privacy values are to be chosen among a fixed set of options. We formally demonstrate that over time, the system converges toward a "fair"state, wherein each individual's preferences are accounted for. Our discrete model is validated by way of a user study, where participants are asked to propose privacy settings for own shared content from a small, discrete set of options.
AB - In this article, we aim to answer an important set of questions about the potential longitudinal effects of repeated sharing and privacy settings decisions over jointly managed content among users in a social network.We model user interactions through a repeated game in a network graph. We present a variation of the one-shot Ultimatum Game, wherein individuals interact with peers to make a decision on a piece of shared content. The outcome of this game is either success or failure, wherein success implies that a satisfactory decision for all parties is made and failure instead implies that the parties could not reach an agreement. Our proposed game is grounded in empirical data about individual decisions in repeated pairwise negotiations about jointly managed content in a social network. We consider both a "continuous"privacy model as well the "discrete"case of a model wherein privacy values are to be chosen among a fixed set of options. We formally demonstrate that over time, the system converges toward a "fair"state, wherein each individual's preferences are accounted for. Our discrete model is validated by way of a user study, where participants are asked to propose privacy settings for own shared content from a small, discrete set of options.
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U2 - 10.1145/3555351
DO - 10.1145/3555351
M3 - Article
AN - SCOPUS:85141077755
SN - 1559-1131
VL - 16
JO - ACM Transactions on the Web
JF - ACM Transactions on the Web
IS - 3
M1 - 13
ER -