DocumentCode :
1921527
Title :
Sentiment classification using phrase patterns
Author :
Fei, Zhongchao ; Liu, Jian ; Wu, Gengfeng
Author_Institution :
Dept. of Comput. Sci., Shanghai Univ., China
fYear :
2004
fDate :
14-16 Sept. 2004
Firstpage :
1147
Lastpage :
1152
Abstract :
This paper presents a phrase pattern-based method in classifying sentiment orientation of text. That is to analyze whether the text expresses a favorable or unfavorable sentiment for a specific subject. In our method, we construct some phrase patterns and calculate their sentiment orientation by unsupervised learning algorithm. When we classify a document, we first add special tags to some words in the text, then match the tags within a sentence with some phrase patterns to get the sentiment orientation of the sentence. At last, we add up the sentiment orientation of each sentence. We classify the text according to this summation. The method achieves an accuracy rate of 86% when used to evaluate sports reviews from some Websites.
Keywords :
computational linguistics; natural languages; pattern classification; text analysis; unsupervised learning; Web site; document classification; pattern classification; phrase pattern-based method; sentiment classification; tag matching; text sentiment orientation; unsupervised learning; word tags; Computer science; Feedback; Information filtering; Information filters; Information technology; Internet; Natural language processing; Pattern matching; Text categorization; Unsupervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Information Technology, 2004. CIT '04. The Fourth International Conference on
Print_ISBN :
0-7695-2216-5
Type :
conf
DOI :
10.1109/CIT.2004.1357349
Filename :
1357349
Link To Document :
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