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Hot Topic Detection in Professional Blogs

  • Erzhong Zhou
  • Ning Zhong
  • Yuefeng Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6890)

Abstract

Topics in professional blogs mainly refer to specific techniques. Today, professional blog websites have been important information sources. However, information overload and the uncertainty of topic hotness evaluation have been obstacles for hot topic detection. The paper proposes a method of detecting hot topics in professional blogs. The proposed method is based on the characteristics of the professional blogs and mainly analyzes candidate topics that are likely to be hot. First, a word network based on high frequency keywords and co-occurrences of the keywords is constructed, and then the candidate topics are extracted by analyzing the structure of the word network. The opinion networks with respect to the topics in different time intervals are subsequently constructed for opinion analysis. Finally, hot topics are identified by computing the user participation degree, opinion communication degree, and timeliness of the candidate topics. Experimental results show the proposed method is feasible and reasonable.

Keywords

Vector Space Model Opinion Communication Topic Detection Keyword Extraction Candidate Topic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Erzhong Zhou
    • 1
  • Ning Zhong
    • 1
    • 2
  • Yuefeng Li
    • 3
  1. 1.International WIC InstituteBeijing University of TechnologyBeijingP.R. China
  2. 2.Department of Life Science and InformaticsMaebashi Institute of TechnologyMaebashiJapan
  3. 3.Faculty of Science and TechnologyQueensland University of TechnologyBrisbaneAustralia

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