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Title: Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis
Authors: Poria, S.
Gelbukh, A.
Cambria, E. 
Yang, P.
Hussain, A.
Durrani, T.
Keywords: emotions
Sentic computing
sentiment analysis
Issue Date: 2012
Citation: Poria, S.,Gelbukh, A.,Cambria, E.,Yang, P.,Hussain, A.,Durrani, T. (2012). Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis. International Conference on Signal Processing Proceedings, ICSP 2 : 1251-1255. ScholarBank@NUS Repository.
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. © 2012 IEEE.
Source Title: International Conference on Signal Processing Proceedings, ICSP
ISBN: 9781467321945
DOI: 10.1109/ICoSP.2012.6491803
Appears in Collections:Staff Publications

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