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Retweeting Prediction Using Meta-Paths Aggregated with Follow Model in Online Social Networks

  • Li WeigangEmail author
  • Jianya Zheng
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 373)

Abstract

Studying the mechanism of retweeting is useful for understanding the information diffusion in Online Social Networks (OSNs). In this paper, we examine a number of topological features that may affect the retweeting behavior. We apply the Follow Model to formulate the user relations and then propose Relationship Commitment Adjacency Matrix (RCAM) to present the connectivity between users in OSNs. We define three meta-paths to identify the people who may retweet. With these meta-paths, various instance-paths are revealed in the retweeting prediction problem. A framework based on Conditional Random Field model is developed and implemented with the data from Sina Weibo. The case study obtains the results of retweeting prediction with the indices of precision larger than 61% and recall larger than 58%.

Keywords

Follow model Online Social Network retweeting prediction Weibo 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.TransLab, Department of Computer ScienceUniversity of BrasiliaBrasiliaBrazil

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