TY - JOUR
T1 - An evolutionary game model for analysis of rumor propagation and control in social networks
AU - Askarizadeh, Mojgan
AU - Tork Ladani, Behrouz
AU - Manshaei, Mohammad Hossein
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/6/1
Y1 - 2019/6/1
N2 - Nowadays, social networks are widely used as fast and ubiquitous media for sharing information. Rumor as unverified information also considerably spreads in social networks. The study of how rumor spreads and how it can be controlled, plays an important role in reducing social and psychological damages of rumor in social networks. Although recent researches have mainly focused on epidemic models and structure of social networks, they ignore the impact of people's decision on rumor process. In this paper, an evolutionary game model is proposed to analyze the rumor process in social network considering the impacts of people's decisions on rumor propagation and control. The model considers a rumor control mechanism via sending anti-rumor messages through rumor control centers. Factors affecting the people's decisions including social anxiety, people's attitude toward rumor/anti-rumor, strength of rumor/anti-rumor, influence of rumor control centers, and participation of people in discussions are studied in the model. The proposed game model is analyzed by replicator dynamics equations and simulation of the imitation update rule on a synthetic (Barabasi–Albert) and two real-world graphs of Twitter and Facebook. We further analyze the model in various environments considering people characteristics and society situation. Also we use a real rumor dataset of Twitter (Pheme dataset) to first compare the trends of people strategies (rumor/anti-rumor spreader and ignorant) derived by the model with the real trends of the traits of people in the rumor spreading on Twitter. Then we conduct a number of sensitivity analysis experiments to show the impact of different factors on rumor process. In fact, we analyze the trends of people strategies in Pheme dataset assuming various possible conditions. The analysis show that propagation of convincing anti-rumor messages and locating rumor control centers impact debunking the rumor. Moreover, it is shown that people attitude toward rumor/anti-rumor has significant impact on rumor spreading. Besides, factors such as social anxiety and strength of rumor accelerates rumor propagation.
AB - Nowadays, social networks are widely used as fast and ubiquitous media for sharing information. Rumor as unverified information also considerably spreads in social networks. The study of how rumor spreads and how it can be controlled, plays an important role in reducing social and psychological damages of rumor in social networks. Although recent researches have mainly focused on epidemic models and structure of social networks, they ignore the impact of people's decision on rumor process. In this paper, an evolutionary game model is proposed to analyze the rumor process in social network considering the impacts of people's decisions on rumor propagation and control. The model considers a rumor control mechanism via sending anti-rumor messages through rumor control centers. Factors affecting the people's decisions including social anxiety, people's attitude toward rumor/anti-rumor, strength of rumor/anti-rumor, influence of rumor control centers, and participation of people in discussions are studied in the model. The proposed game model is analyzed by replicator dynamics equations and simulation of the imitation update rule on a synthetic (Barabasi–Albert) and two real-world graphs of Twitter and Facebook. We further analyze the model in various environments considering people characteristics and society situation. Also we use a real rumor dataset of Twitter (Pheme dataset) to first compare the trends of people strategies (rumor/anti-rumor spreader and ignorant) derived by the model with the real trends of the traits of people in the rumor spreading on Twitter. Then we conduct a number of sensitivity analysis experiments to show the impact of different factors on rumor process. In fact, we analyze the trends of people strategies in Pheme dataset assuming various possible conditions. The analysis show that propagation of convincing anti-rumor messages and locating rumor control centers impact debunking the rumor. Moreover, it is shown that people attitude toward rumor/anti-rumor has significant impact on rumor spreading. Besides, factors such as social anxiety and strength of rumor accelerates rumor propagation.
KW - Evolutionary game
KW - Rumor control
KW - Rumor propagation
KW - Social network
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U2 - 10.1016/j.physa.2019.01.147
DO - 10.1016/j.physa.2019.01.147
M3 - Article
AN - SCOPUS:85062010265
SN - 0378-4371
VL - 523
SP - 21
EP - 39
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
ER -