Title
Modeling social network behavior spread based on group cohesion under uncertain environment
Abstract
Behavior is autonomous, convergent, and uncertain, which brings challenges to the modeling of social network behavior spread. In this article, we propose a behavior spread model based on group cohesion under uncertain environments. First, for behavioral convergence, we define group cohesion to quantify the convergent effects of group. Second, based on the game theory to model the autonomy of behavior, according to the characteristics of the game payoffs changing with time and the depth of spread, and integrating group cohesion, a dynamic game payoffs calculation method is designed. Finally, aiming at the uncertainty of behavior, a group behavior spread model based on random utility theory is established. Experiments on multiple real social network behavior spread datasets demonstrate the effectiveness of the proposed model in modeling and predicting behavior spread processes under uncertain environments.
Year
DOI
Venue
2022
10.1002/cpe.7101
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
Keywords
DocType
Volume
game theory, group behavior, group cohesion, spread model, uncertainty
Journal
34
Issue
ISSN
Citations 
21
1532-0626
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Weimin Li16325.40
Zhibin Deng200.34
Xiaokang Zhou321.45
Qun Jin400.68
Bin Sheng500.34