Characterizing Buzz and Sentiment in Internet Sources: Linguistic Summaries and Predictive Behaviors

  • Richard M. Tong
  • Ronald R. Yager
Part of the The Information Retrieval Series book series (INRE, volume 20)


Internet sources, such as newsgroups, message boards, and blogs, are an under-exploited resource for developing analyses of community and market responses to everything from consumer products and services, to current events and politics. In this paper, we present an overview of our exploration of effective ways of characterizing this large volume of information. In our approach, we first create time-series that represent the subjects, opinions, and attitudes expressed in the Internet sources, and then generate “Linguistic Summaries” that provide natural and easily understood descriptions of the behaviors exhibited by these time-series.


Internet buzz sentiment linguistic summaries marketing research intelligence analysis data mining text mining fuzzy sets time-series analysis 


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Copyright information

© Springer 2006

Authors and Affiliations

  • Richard M. Tong
    • 1
  • Ronald R. Yager
    • 2
  1. 1.Tarragon Consulting CorporationBerkeleyUSA
  2. 2.Machine Intelligence InstituteIona CollegeNew RochelleUSA

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