Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis
Published 1 October 2012Open access
Soujanya Poria, Alexander Gelbukh, Erik Cambria, Peipei Yang, Amir Hussain, T.S. Durrani
Citations98
SJR quartileQ4
SJR score0.11
SNIP0.06
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TL;DR
This work reports a work on automatically merging SenticNet and WordNet-Affect by assigning emotion labels to more than 2700 concepts, which is a major step towards merging these two resources.
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.
Keywords
Computer Science
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