An Agent-based Model for Exploring Retweeting Behaviors based on Multiple Social Relationships on Twitter Platform
In this paper,we focus on understanding and modeling user”s retweeting behavior through implicit social relationships and its effects on information diffusion on Twitter social network.To achieve this goal,we first define two types of influences between users as Authority degree and Familiarity degree,corresponding to the unidirectional-follow and bidirectional-follow relationship on Twitter social network.And then we consider the influence of a tweet from its retweeted number and retweeting similarity.The combination of user influence and twitter influence together determine which tweet to be retweeted through the interactions between users.Further,we set up a tweets queue with limited size to model a user”s limited attention,because one can only pay attention to a portion of tweets shared on his/her homepage.On this basis,we build an agent-based model which simulates the user”s retweeting behavior-based information propagation by incorporating both user influence and tweet influence into the key process of selecting a tweet.By comparing statistical characteristics of multiplex networks between the simulated result and actual data,we have confirmed the applicability of our proposed model and methods on exploring retweeting behaviors through implicit social relationships on Twitter.
information propagation retweeting behavior social relationship agent-based model
Bin Jiang Chao Yang Lei Wang Renfa Li
College of Computer Science and Electronic Engineering Hunan University Changsha,Hunan,China Business School Hunan University Changsha,Hunan,China
国内会议
第10届全国计算机支持的协同工作学术会议暨中国计算机学会协同计算专委年度工作会议
太原
英文
561-568
2015-08-28（万方平台首次上网日期，不代表论文的发表时间）