Modeling the Formation of User Replying Network on Government Microblogs: An Exponential Random Graph Model

With the rapid development of social media, people get increasingly involved in public affairs through social networks, e.g., microblogs. Although social network plays a significant role in public affairs, some online government communities lack sufficient response, triggering an negative environment for policy decision process. In order to foster a healthy online government community, understanding the mechanism and drivers of user interaction becomes critical, especially for user to user interaction. We build a theoretical model to explain the formation of user to user network and understanding the underlying mechanism of why a user would be replied by others in government microblogging. We collect the user information, posted microblogs and the replies from government microblogs in 10 different areas to construct user replying networks. By using exponential random graph model (GRGM), we delve into the mechanism of how the network structures and node attributes affect the formation of user replying networks. Our experimental results validate that the mutual, homophily and emotional effect are the main drivers of users replying behavior.

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