Cross-domain co-extraction of sentiment and topic lexicons
Date
2012
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Abstract
The goal is automatic extraction of relevant terms from a domain of interest. In the past few years, opinion mining and sentiment analysis have attracted much attention in natural language processing and information retrieval. The proposed method can utilize useful labeled data from the source domain as well as exploit the relationships between the topic and sentiment words to propagate information for lexicon construction in the target domain. Domain adaptation aims at transferring knowledge across domains where data distributions may be different. This model extracts both topic and sentiment words and also allows non-adjective sentiment words, achieving much better results on cross-domain lexicon extraction.
Description
Meeting: 50th Annual Meeting of Association for Computational Linguistics (ACL'12)
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Conference Paper
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Keywords
SENTIMENT ANALYSIS, MACHINE LEARNING, ALGORITHMS
Citation
Fangtao Li, Sinno Jialin Pan, Ou Jin, Qiang Yang, & Xiaoyan Zhu (2012). Cross-Domain Co-Extraction of Sentiment and Topic Lexicons. Proceedings of the 50th Annual Meeting of Association for Computational Linguistics (ACL'12)