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Predicting Popularity of Topic Based on Similarity Relation and Co-occurrence Relation

  • Lu DengEmail author
  • Qiang Liu
  • Jing Xu
  • Jiuming Huang
  • Bin Zhou
  • Yan Jia
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 686)

Abstract

Interaction behaviors of users on different platforms on the Internet make user-generated content spread widely and become popular. How to model and predict the popularity of topic concerned by users is vital for many fields. Aiming at the problem of topic popularity prediction on microblog platform, a popularity prediction method based on similar topics and co-occurrence topics is proposed. The method is further evaluated with the Sina Weibo dataset. The experimental results show that our method can have relatively better performance in predicting topic popularity than the baseline methods.

Keywords

Popularity prediction Similarity relation Co-occurrence relation 

Notes

Acknowledgements

The work described in this paper is partially supported by National Key Fundamental Research and Development Program (No. 2013CB329601, No. 2013CB329602, No. 2013CB329604) and National Natural Science Foundation of China (No. 61502517, No. 61372191, No. 61572492, No. 61502517), 863 Program of China (Grant No. 2012AA01A401, 2012AA01A402, 2012AA013002), Project funded by China Postdoctoral Science Foundation (2013M542560, 2015T81129).

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Lu Deng
    • 1
    Email author
  • Qiang Liu
    • 1
  • Jing Xu
    • 1
  • Jiuming Huang
    • 1
  • Bin Zhou
    • 1
  • Yan Jia
    • 1
  1. 1.College of ComputerNational University of Defense TechnologyChangshaChina

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