Sentiment Analyzer: Extracting sentiments about a given topic using natural language processing techniques

被引：242

作者：

Yi, JH ^{[1
]}

Nasukawa, T ^{[1
]}

Bunescu, R ^{[1
]}

Niblack, W ^{[1
]}

机构：

[1] IBM Corp, Almaden Res Ctr, San Jose, CA 95120 USA

来源：

THIRD IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS | 2003年

关键词：

D O I：

10.1109/ICDM.2003.1250949

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：427 / 434

页数：8

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