Modeling and Analysis of Rumor Control Strategies in Social Networks

Todays, although social networks are used for extensive information sharing, spreading rumors has also been accelerated and become a serious problem. Rumor control can be accomplished through either hard or soft control strategies. The former uses depriving actions like blocking rumor spreaders, while the latter tries to persuade people personally avoiding rumor propagation by increasing their knowledge and awareness. Although there are some proposals for rumor control in social networks, suitable frameworks for modeling and analysis of rumor control strategies and methods with proper consideration of the effective factors is still a need. This study introduces a rumor propagation model based on evolutionary game theory along with a number of soft and hard rumor control methods. Using the proposed model, we simulate and analyze rumor control methods considering different environmental, personal, and content-related factors that may influence people's decisions about rumors. The simulation is conducted on a Twitter graph according to various society conditions. One of the findings is that the soft rumor control strategy is generally more effective than the hard rumor control strategy. The proposed model itself and the conducted analysis can be adopted for developing and deploying effective rumor control mechanisms in social network systems.