Sentiment analyzer: extracting sentiments about a given topic using natural language processing techniques
Published 30 March 2004
Junbo Yi, Tetsuya Nasukawa, Răzvan Bunescu, W. Niblack
Citations720
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TL;DR
This work presents sentiment analyzer (SA) that extracts sentiment (or opinion) about a subject from online text documents using natural language processing (NLP) techniques.
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 document about a subject, SA detects all references to the given subject, and determines sentiment in each of the references using natural language processing (NLP) techniques. Our sentiment analysis consists of 1) a topic specific feature term extraction, 2) sentiment extraction, and 3) (subject, sentiment) association by relationship analysis. SA utilizes two linguistic resources for the analysis: the sentiment lexicon and the sentiment pattern database. The performance of the algorithms was verified on online product review articles ("digital camera" and "music" reviews), and more general documents including general Webpages and news articles.
Keywords
Computer Science
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