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Using WordNet’s Semantic Relations for Opinion Detection in Blogs

  • Malik Muhammad Saad Missen
  • Mohand Boughanem
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5478)

Abstract

The Opinion Detection from blogs has always been a challenge for researchers. One of the challenges faced is to find such documents that specifically contain opinion on users’ information need. This requires text processing on sentence level rather than on document level. In this paper, we have proposed an opinion detection approach. The proposed approach focuses on above problem by processing documents on sentence level using different semantic similarity relations of WordNet between sentence words and list of weighted query words expanded through encyclopedia Wikipedia. According to initial results, our approach performs well with MAP of 0.28 and P@10 of 0.64 with improvement of 27% over baseline results. TREC Blog 2006 data is used as test data collection.

Keywords

Opinion Detection Blogs WordNet Semantic Relatedness 

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Malik Muhammad Saad Missen
    • 1
  • Mohand Boughanem
    • 1
  1. 1.Université de Toulouse IRIT ToulouseFrance

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