JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2014, Vol. 49 ›› Issue (11): 31-36.doi: 10.6040/j.issn.1671-9352.3.2014.305

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Personalized ranking of Micro-blogging forwarders

KUANG Chong, LIU Zhi-yuan, SUN Mao-song   

  1. State Key Laboratory of Intelligent Technology and Systems; Tsinghua National Laboratory for Information Science and Technology; Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
  • Received:2014-08-28 Revised:2014-10-24 Online:2014-11-20 Published:2014-11-25

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Abstract: The repost action is the main way for information spreading in Micro-blogging platform. Nowadays, many works have been done focusing on the repost behaviors' analysis and prediction. However, the problem about how to find the users who are the most likely to repost a given Micro-blog remains unsolved. In this paper, a general predictor, which combines Bayesian Personalized Ranking optimization criterion with Factorization Machines was presented to predict the reposter of a microblog. Furthermore, factors which affect a user to be a reposter were analyzed in details. With these facts, prediction of the reposters over large-scale real datasets was conducted. The experiment proves that this method can improve the effect of the prediction obviously. Meanwhile, method based on pair-wise and feature-related can solve the prediction problem more efficiently.

Key words: Micro-blog, personalized ranking, repost

CLC Number: 

  • TP391
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