Detecting Community Pacemakers of Burst Topic in Twitter

摘要：

　　Twitter has become one of largest social networks for users to broadcast burst topics.Influential users usually have a large number of followers and play an important role in the diffusion of burst topic.There have been many studies on how to detect influential users.However,traditional influential users detection approaches have largely ignored influential users in user community.In this paper,we investigate the problem of detecting community pacemakers.Community pacemakers are defined as the influential users that promote early diffusion in the user community of burst topic.To solve this problem,we present DCPBT,a framework that can detect community pacemakers in burst topics.In DCPBT,a burst topic user graph model is proposed,which can represent the topology structure of burst topic propagation across a large number of Twitter users.Based on the model,a user community detection algorithm based on random walk is applied to discover user community.For large-scale user community,we propose a ranking method to detect community pacemakers in each large-scale user community.To test our framework,we conduct the framework over Twitter burst topic detection system.Experimental results show that our method is more effective to detect the users that influence other users and promote early diffusion in the early stages of burst topic.

关键词： Twitter Burst topic User graph model Community pacemakers

作者: Guozhong Dong Wu Yang Feida Zhu Wei Wang

作者单位: Information Security Research Center,Harbin Engineering University,Harbin,China Singapore Management University,Singapore,Singapore

会议类型: 国际会议

会议名称: International Asia-Pacific Web Conference(第18届国际亚太互联网大会)

会议地点: 苏州

会议语种:英文

页码: 245-255

在线出版日期: 2016-09-23（万方平台首次上网日期，不代表论文的发表时间）