Predicting retweet behavior in weibo social network

  • Authors:

  • Hongbo Zhang;Qun Zhao;Hongyan Liu;Ke xiao;Jun He;Xiaoyong Du;Hong Chen

  • Affiliations:

  • Key Labs of Data Engineering and Knowledge Engineering, Ministry of Education, China,School of Information, Renmin University of China, China;Key Labs of Data Engineering and Knowledge Engineering, Ministry of Education, China,School of Information, Renmin University of China, China;School of Economics and Management, Tsinghua University, China;School of Information, Renmin University of China, China;Key Labs of Data Engineering and Knowledge Engineering, Ministry of Education, China,School of Information, Renmin University of China, China;Key Labs of Data Engineering and Knowledge Engineering, Ministry of Education, China,School of Information, Renmin University of China, China;Key Labs of Data Engineering and Knowledge Engineering, Ministry of Education, China,School of Information, Renmin University of China, China

  • Venue:
  • WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
  • Year:
  • 2012

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Abstract

Retweeting ensures the information diffusion in micro-blog services. By this simple way, it is convenient for a user to share and spread interesting information in the whole network. In this paper, we consider many features to compute the probability that a user retweets a tweet. With the probability, we build a retweet model to predict the number of possible-views of a tweet. The model is based on the theory of random walks. Experiments conducted on real dataset show that the proposed method has a good performance than the traditional prediction methods.