Aspect summarization from blogsphere for social study

Chia Hui Chang, Kun Chang Tsai

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

3 Scopus citations

Abstract

In this paper, we study the problem of summarizing reasons from blogsphere for social study. We regard weblogs as a source for collecting non-discrete public opinions, where genuine reasons/aspects can be found. To extract the reason inside the blogs, we define four tasks: irrelevant blog filtering, reason/non-reason classification, polarity identification, and reason summarization. We solve the reason/non-reason classification problem by selecting a set of topic related words and brief the reasons by clustering paragraphs containing aspects after sentiment classification. Initial experiments on two topics show an encouraging result on the proposed framework.

Original languageEnglish
Title of host publicationICDM Workshops 2007 - Proceedings of the 17th IEEE International Conference on Data Mining Workshops
Pages9-14
Number of pages6
DOIs
StatePublished - 2007
Event17th IEEE International Conference on Data Mining Workshops, ICDM Workshops 2007 - Omaha, NE, United States
Duration: 28 Oct 200731 Oct 2007

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786

Conference

Conference17th IEEE International Conference on Data Mining Workshops, ICDM Workshops 2007
Country/TerritoryUnited States
CityOmaha, NE
Period28/10/0731/10/07

Keywords

  • Opinion extraction
  • Reason summarization
  • Sentiment classicization
  • Social study
  • Text mining
  • Weblogs

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