Sentiment analyzer: Extracting sentiments about a given topic using natural language processing techniques (2003)
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| Venue: | In IEEE Intl. Conf. on Data Mining (ICDM |
| Citations: | 60 - 1 self |
BibTeX
@INPROCEEDINGS{Yi03sentimentanalyzer:,
author = {Jeonghee Yi and Tetsuya Nasukawa and Razvan Bunescu and Wayne Niblack},
title = {Sentiment analyzer: Extracting sentiments about a given topic using natural language processing techniques},
booktitle = {In IEEE Intl. Conf. on Data Mining (ICDM},
year = {2003},
pages = {427--434}
}
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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 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. 1.
