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EMNLP
2006

Fully Automatic Lexicon Expansion for Domain-oriented Sentiment Analysis

14 years 1 months ago
Fully Automatic Lexicon Expansion for Domain-oriented Sentiment Analysis
This paper proposes an unsupervised lexicon building method for the detection of polar clauses, which convey positive or negative aspects in a specific domain. The lexical entries to be acquired are called polar atoms, the minimum human-understandable syntactic structures that specify the polarity of clauses. As a clue to obtain candidate polar atoms, we use context coherency, the tendency for same polarities to appear successively in contexts. Using the overall density and precision of coherency in the corpus, the statistical estimation picks up appropriate polar atoms among candidates, without any manual tuning of the threshold values. The experimental results show that the precision of polarity assignment with the automatically acquired lexicon was 94% on average, and our method is robust for corpora in diverse domains and for the size of the initial lexicon.
Hiroshi Kanayama, Tetsuya Nasukawa
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where EMNLP
Authors Hiroshi Kanayama, Tetsuya Nasukawa
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