DocumentCode :
3301537
Title :
Disambiguating sentiment ambiguous adjectives
Author :
Wu, Yunfang ; Wang, Miao ; Jin, Peng
Author_Institution :
Inst. of Comput. Linguistics, Peking Univ., Beijing
fYear :
2008
fDate :
19-22 Oct. 2008
Firstpage :
1
Lastpage :
8
Abstract :
This paper makes a systematic study on disambiguating sentiment ambiguous adjectives within context in real text, which is an interaction between word sense disambiguation and sentiment analysis. We firstly address the issue of inter-annotator agreement on assigning semantic orientations to word occurrences in real text. Secondly we demonstrate that co-occurring sentiment monosemous adjectives can not effectively disambiguate sentiment ambiguous adjectives. Then collocation-based disambiguation and support vector machine (SVM) algorithm are exploited on the task of disambiguation. We present a new approach of combining collocation information and SVM to disambiguate sentiment ambiguous words. The experimental results show that the combining approach of Coll+SVM outperforms both collocation-based method and SVM algorithm.
Keywords :
natural language processing; support vector machines; collocation-based disambiguation; disambiguating sentiment ambiguous adjectives; interannotator agreement; sentiment analysis; support vector machine; word sense disambiguation; Computational linguistics; Information analysis; Mutual information; Natural language processing; Natural languages; Sawing machines; Speech analysis; Support vector machines; Sentiment analysis; collocation; inter-annotator agreement; sentiment ambiguous words; support vector machine; word sense disambiguation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Language Processing and Knowledge Engineering, 2008. NLP-KE '08. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4515-8
Electronic_ISBN :
978-1-4244-2780-2
Type :
conf
DOI :
10.1109/NLPKE.2008.4906816
Filename :
4906816
Link To Document :
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