Sentiment Analyzer: Extracting Sentiments about a Given Topic using Natural Language Processing Techniques

  • Authors:
  • Jeonghee Yi;Tetsuya Nasukawa;Razvan Bunescu;Wayne Niblack

  • Affiliations:
  • -;-;-;-

  • Venue:
  • ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
  • Year:
  • 2003

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Abstract

We present Sentiment Analyzer (SA) that extracts sentiment(or opinion) about a subject from online text documents.Instead of classifying the sentiment of an entire documentabout a subject, SA detects all references to the givensubject, and determines sentiment in each of the referencesusing natural language processing (NLP) techniques. Oursentiment analysis consists of 1) a topic specific featureterm extraction, 2) sentiment extraction, and 3) (subject,sentiment) association by relationship analysis. SA utilizestwo linguistic resources for the analysis: the sentiment lexiconand the sentiment pattern database. The performanceof the algorithms was verified on online product review articles("digital camera" and "music" reviews), and moregeneral documents including general webpages and newsarticles.