Understanding user-to-User interaction on government microblogs: An exponential random graph model with the homophily and emotional effect
作者：
Highlights：
• Factors influencing user-to-user interaction on microblogs are examined.
• Effects of network structure, user’s social capital and online sentiment are included.
• Data from Sina Weibo is collected to test the model using ERGM.
• Users with higher influence are more likely to get replies but not giving replies.
• Users with extreme emotion are more likely to get and give replies.
摘要
•Factors influencing user-to-user interaction on microblogs are examined.•Effects of network structure, user’s social capital and online sentiment are included.•Data from Sina Weibo is collected to test the model using ERGM.•Users with higher influence are more likely to get replies but not giving replies.•Users with extreme emotion are more likely to get and give replies.
论文关键词：Government microblogs,User interaction,Exponential random graph,Homophily,Online emotion
论文评审过程：Received 26 September 2019, Revised 30 December 2019, Accepted 16 February 2020, Available online 27 February 2020, Version of Record 6 May 2020.
论文官网地址：https://doi.org/10.1016/j.ipm.2020.102229
