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