TY - GEN
T1 - An Ultimatum Game Model for the Evolution of Privacy in Jointly Managed Content
AU - Rajtmajer, Sarah
AU - Squicciarini, Anna
AU - Such, Jose M.
AU - Semonsen, Justin
AU - Belmonte, Andrew
N1 - Funding Information:
Acknowledgements. Portions of Dr. Squicciarini’s and Mr. Semonsen’s work were funded by Army Research Office under the auspices of Grant W911NF-13-1-0271. Portions of Dr. Squicciarini’s work were additionally supported by a National Science Foundation grant 1453080. Dr. Such was supported by the EPSRC under grant EP/M027805/2.
Publisher Copyright:
© 2017, Springer International Publishing AG.
PY - 2017
Y1 - 2017
N2 - Content sharing in social networks is now one of the most common activities of internet users. In sharing content, users often have to make access control or privacy decisions that impact other stakeholders or co-owners. These decisions involve negotiation, either implicitly or explicitly. Over time, as users engage in these interactions, their own privacy attitudes evolve, influenced by and consequently influencing their peers. In this paper, we present a variation of the one-shot Ultimatum Game, wherein we model individual users interacting with their peers to make privacy decisions about shared content. We analyze the effects of sharing dynamics on individuals’ privacy preferences over repeated interactions of the game. We theoretically demonstrate conditions under which users’ access decisions eventually converge, and characterize this limit as a function of inherent individual preferences at the start of the game and willingness to concede these preferences over time. We provide simulations highlighting specific insights on global and local influence, short-term interactions and the effects of homophily on consensus.
AB - Content sharing in social networks is now one of the most common activities of internet users. In sharing content, users often have to make access control or privacy decisions that impact other stakeholders or co-owners. These decisions involve negotiation, either implicitly or explicitly. Over time, as users engage in these interactions, their own privacy attitudes evolve, influenced by and consequently influencing their peers. In this paper, we present a variation of the one-shot Ultimatum Game, wherein we model individual users interacting with their peers to make privacy decisions about shared content. We analyze the effects of sharing dynamics on individuals’ privacy preferences over repeated interactions of the game. We theoretically demonstrate conditions under which users’ access decisions eventually converge, and characterize this limit as a function of inherent individual preferences at the start of the game and willingness to concede these preferences over time. We provide simulations highlighting specific insights on global and local influence, short-term interactions and the effects of homophily on consensus.
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U2 - 10.1007/978-3-319-68711-7_7
DO - 10.1007/978-3-319-68711-7_7
M3 - Conference contribution
AN - SCOPUS:85032873611
SN - 9783319687100
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 112
EP - 130
BT - Decision and Game Theory for Security - 8th International Conference, GameSec 2017, Proceedings
A2 - Kiekintveld, Christopher
A2 - Schauer, Stefan
A2 - An, Bo
A2 - Rass, Stefan
A2 - Fang, Fei
PB - Springer Verlag
T2 - 8th International Conference on Decision and Game Theory for Security, GameSec 2017
Y2 - 23 October 2017 through 25 October 2017
ER -