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Autor:
Flekova, Lucie; Ruppert, Eugen; Preotiuc-Pietro, Daniel:

Titel:
Analyzing domain suitability of a sentiment lexicon by identifying distributionally bipolar words

Quelle:
In: Association for Computational Linguistics (Hrsg.): 6th workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA 2015) Red Hook, NY : Association for Computational Linguistics (2015) , 77-84

URL des Volltextes:
http://www.emnlp2015.org/proceedings/WASSA/WASSA-2015.pdf#page=89

Sprache:
Englisch

Dokumenttyp:
4. Beiträge in Sammelwerken; Tagungsband/Konferenzbeitrag/Proceedings

Schlagwörter:
Automatisierung, Computerlinguistik, Emotion, Kommunikation, Lexikographie, Lexikon, Online, Qualität, Soziale Software, Textanalyse, Thesaurus


Abstract(original):
Contemporary sentiment analysis approaches rely on lexicon based methods. This is mainly due to their simplicity, although the best empirical results can be achieved by more complex techniques. We introduce a method to assess suitability of generic sentiment lexicons for a given domain, namely to identify frequent bigrams where a polar word switches polarity. Our bigrams are scored using Lexicographers Mutual Information and leveraging large automatically obtained corpora. Our score matches human perception of polarity and demonstrates improvements in classification results using our enhanced context-aware method. Our method enhances the assessment of lexicon based sentiment detection and can be further userd to quantify ambiguous words. (DIPF/Orig.)


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last modified Nov 11, 2016