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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Using WordNet’s Semantic Relations for Opinion Detection in Blogs
verfasst von : Malik Muhammad Saad Missen, Mohand Boughanem
Erschienen in: Advances in Information Retrieval
Verlag: Springer Berlin Heidelberg
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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.