Group Behavior Prediction and Evolution in Social Networks

Jingchao Wang, Xinyi Zhang, Weimin Li, Xiao Yu, Fangfang Liu, Qun Jin

Abstract: Group behavior prediction and evolution in social networks aims to accurately predict and model trends and patterns of group behavior through detailed analysis of massive user data, which is of great significance to the formulation of marketing strategies, user experience, and business strategies. Therefore, experts in various fields are actively exploring the potential of social network data to develop more accurate group behavior prediction and evolution models. This article provides an overview of these studies and explores the challenges and opportunities faced by group behavior prediction and evolution in social networks.