| Title | Game Theoretic Opinion Models and Their Application in Processing Disinformation |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Guo, Zhen, Cho, Jin–Hee |
| Conference Name | 2021 IEEE Global Communications Conference (GLOBECOM) |
| Date Published | dec |
| Keywords | disinformation, game theoretic security, human factors, Information filters, Media, opinion dynamics, Predictive Metrics, pubcrawl, Resists, Scalability, social networking (online), Solid modeling, Solids, subjective opinion, uncer-tainty, Uncertainty |
| Abstract | Disinformation, fake news, and unverified rumors spread quickly in online social networks (OSNs) and manipulate people's opinions and decisions about life events. The solid mathematical solutions of the strategic decisions in OSNs have been provided under game theory models, including multiple roles and features. This work proposes a game-theoretic opinion framework to model subjective opinions and behavioral strategies of attackers, users, and a defender. The attackers use information deception models to disseminate disinformation. We investigate how different game-theoretic opinion models of updating people's subject opinions can influence a way for people to handle disinformation. We compare the opinion dynamics of the five different opinion models (i.e., uncertainty, homophily, assertion, herding, and encounter-based) where an opinion is formulated based on Subjective Logic that offers the capability to deal with uncertain opinions. Via our extensive experiments, we observe that the uncertainty-based opinion model shows the best performance in combating disinformation among all in that uncertainty-based decisions can significantly help users believe true information more than disinformation. |
| DOI | 10.1109/GLOBECOM46510.2021.9685197 |
| Citation Key | guo_game_2021 |
Game Theoretic Opinion Models and Their Application in Processing Disinformation