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Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Author(s): Poria, Soujanya
Gelbukh, Alexander
Cambria, Erik
Yang, Peipei
Hussain, Amir
Durrani, Tariq
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Title: Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis
Citation: Poria S, Gelbukh A, Cambria E, Yang P, Hussain A & Durrani T (2012) Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis In: International Conference on Signal Processing Proceedings, ICSP, Piscataway, NJ: IEEE. 2012 IEEE 11th International Conference on Signal Processing (ICSP), 21.10.2012 - 25.10.2012, Beijing, China, pp. 1251-1255.
Issue Date: 2012
Series/Report no.: 2
Conference Name: 2012 IEEE 11th International Conference on Signal Processing (ICSP)
Conference Dates: 2012-10-21T00:00:00Z
Conference Location: Beijing, China
Abstract: SenticNet is currently one of the most comprehensive freely available semantic resources for opinion mining. However, it only provides numerical polarity scores, while more detailed sentiment-related information for its concepts is often desirable. Another important resource for opinion mining and sentiment analysis is WordNet-Affect, which in turn lacks quantitative information. We report a work on automatically merging these two resources by assigning emotion labels to more than 2700 concepts.
Status: Book Chapter: author post-print (pre-copy editing)
Rights: Copyright 2012 IEEE. Publisher policy states that authors are free to post the accepted version of their article on their personal Web sites or those of their employers.

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