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
Sentiment analysisComputer scienceLexiconNatural language processingSubject (documents)Artificial intelligenceNatural languageFeature extractionInformation retrievalWorld Wide Web
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Publication Info
- Year
- 2004
- Type
- article
- Pages
- 427-434
- Citations
- 719
- Access
- Closed
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Cite This
Junbo Yi,
Tetsuya Nasukawa,
Răzvan Bunescu
et al.
(2004).
Sentiment analyzer: extracting sentiments about a given topic using natural language processing techniques.
, 427-434.
https://doi.org/10.1109/icdm.2003.1250949
Identifiers
- DOI
- 10.1109/icdm.2003.1250949