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Analyzing group dynamics for incidental topics in online social networks

  • Xi'an Jiaotong University
  • Tsinghua University
  • Xi'an University of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Groups discussing popular topics in online social networks are of great interests recently. In this paper, we measure the dynamics of the online groups discussing incidental popular topics and present method for predicting the dynamic sizes of incidental topic groups. It is found that the dynamic sizes of incidental topic groups follow the law of heavy-tail. Based on the heavy-tailed theory a prediction method is developed for analyzing the dynamics of this type of groups. The models and methods developed in the paper are validated using the actual data from SOHU blog sites, one of the most influential blog sites in China. The experiment results show that the method can predict the dynamic size of incidental topic groups with both short and long time scales.

Original languageEnglish
Title of host publication2010 8th World Congress on Intelligent Control and Automation, WCICA 2010
Pages1941-1946
Number of pages6
DOIs
StatePublished - 2010
Event2010 8th World Congress on Intelligent Control and Automation, WCICA 2010 - Jinan, China
Duration: 7 Jul 20109 Jul 2010

Publication series

NameProceedings of the World Congress on Intelligent Control and Automation (WCICA)

Conference

Conference2010 8th World Congress on Intelligent Control and Automation, WCICA 2010
Country/TerritoryChina
CityJinan
Period7/07/109/07/10

Keywords

  • Heavy-tail
  • Information propagation
  • Online social networks
  • Topic group dynamics
  • Topic tracking

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