TY - JOUR
T1 - Rumor Transmission in Online Social Networks Under Nash Equilibrium of a Psychological Decision Game
AU - Liu, Wenjia
AU - Wang, Jian
AU - Ouyang, Yanfeng
N1 - Funding Information:
The authors thank the editor and two anonymous referees for their valuable suggestions. The first author was a visiting doctoral student at Illinois while this research was conducted. The first author also thanks Mr. Ruifeng She (Ph.D. student at Illinois) for his comments and help.
Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2022/12
Y1 - 2022/12
N2 - This paper investigates rumor transmission over online social networks, such as those via Facebook or Twitter, where users liberally generate visible content to their followers, and the attractiveness of rumors varies over time and gives rise to opposition such as counter-rumors. All users in social media platforms are modeled as nodes in one of five compartments of a directed random graph: susceptible, hesitating, infected, mitigated, and recovered (SHIMR). The system is expressed with edge-based formulation and the transition dynamics are derived as a system of ordinary differential equations. We further allow individuals to decide whether to share, or disregard, or debunk the rumor so as to balance the potential gain and loss. This decision process is formulated as a game, and the condition to achieve mixed Nash equilibrium is derived. The system dynamics under equilibrium are solved and verified based on simulation results. A series of parametric analyses are conducted to investigate the factors that affect the transmission process. Insights are drawn from these results to help social media platforms design proper control strategies that can enhance the robustness of the online community against rumors.
AB - This paper investigates rumor transmission over online social networks, such as those via Facebook or Twitter, where users liberally generate visible content to their followers, and the attractiveness of rumors varies over time and gives rise to opposition such as counter-rumors. All users in social media platforms are modeled as nodes in one of five compartments of a directed random graph: susceptible, hesitating, infected, mitigated, and recovered (SHIMR). The system is expressed with edge-based formulation and the transition dynamics are derived as a system of ordinary differential equations. We further allow individuals to decide whether to share, or disregard, or debunk the rumor so as to balance the potential gain and loss. This decision process is formulated as a game, and the condition to achieve mixed Nash equilibrium is derived. The system dynamics under equilibrium are solved and verified based on simulation results. A series of parametric analyses are conducted to investigate the factors that affect the transmission process. Insights are drawn from these results to help social media platforms design proper control strategies that can enhance the robustness of the online community against rumors.
KW - Directed networks
KW - Edge-based information model
KW - Nash equilibrium
KW - Rumor transmission
KW - Societal behavior
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U2 - 10.1007/s11067-022-09574-9
DO - 10.1007/s11067-022-09574-9
M3 - Article
C2 - 35791406
AN - SCOPUS:85133294105
SN - 1566-113X
VL - 22
SP - 831
EP - 854
JO - Networks and Spatial Economics
JF - Networks and Spatial Economics
IS - 4
ER -