TY - GEN
T1 - Power Law Public Goods Game for Personal Information Sharing in News Commentaries
AU - Griffin, Christopher
AU - Rajtmajer, Sarah
AU - Umar, Prasanna
AU - Squicciarini, Anna
N1 - Funding Information:
Acknowledgements. Portions of Griffin’s work were supported by the National Science Foundation under grant CMMI-1463482. Griffin also wishes to thank A. Belmonte for the helpful discussion. Dr. Squicciarini’s work is partially funded by the National Science Foundation under grant 1453080. Dr. Squicciarini and Dr. Rajtmajer are also partially supported by PSU Seed grant 425-02.
Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - We propose a public goods game model of user sharing in an online commenting forum. In particular, we assume that users who share personal information incur an information cost but reap the benefits of a more extensive social interaction. Freeloaders benefit from the same social interaction but do not share personal information. The resulting public goods structure is analyzed both theoretically and empirically. In particular, we show that the proposed game always possesses equilibria and we give sufficient conditions for pure strategy equilibria to emerge. These correspond to users who always behave the same way, either sharing or hiding personal information. We present an empirical analysis of a relevant data set, showing that our model parameters can be fit and that the proposed model has better explanatory power than a corresponding null (linear) model of behavior.
AB - We propose a public goods game model of user sharing in an online commenting forum. In particular, we assume that users who share personal information incur an information cost but reap the benefits of a more extensive social interaction. Freeloaders benefit from the same social interaction but do not share personal information. The resulting public goods structure is analyzed both theoretically and empirically. In particular, we show that the proposed game always possesses equilibria and we give sufficient conditions for pure strategy equilibria to emerge. These correspond to users who always behave the same way, either sharing or hiding personal information. We present an empirical analysis of a relevant data set, showing that our model parameters can be fit and that the proposed model has better explanatory power than a corresponding null (linear) model of behavior.
UR - http://www.scopus.com/inward/record.url?scp=85076502585&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85076502585&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-32430-8_12
DO - 10.1007/978-3-030-32430-8_12
M3 - Conference contribution
AN - SCOPUS:85076502585
SN - 9783030324292
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 184
EP - 195
BT - Decision and Game Theory for Security - 10th International Conference, GameSec 2019, Proceedings
A2 - Alpcan, Tansu
A2 - Vorobeychik, Yevgeniy
A2 - Baras, John S.
A2 - Dán, György
PB - Springer
T2 - 10th International Conference on Decision and Game Theory for Security, GameSec 2019
Y2 - 30 October 2019 through 1 November 2019
ER -