Publication | Closed Access
SenticNet: A Publicly Available Semantic Resource for Opinion Mining
254
Citations
14
References
2010
Year
EngineeringMultimodal Sentiment AnalysisSemantic WebCorpus LinguisticsSentiment AnalysisText MiningNatural Language ProcessingInformation RetrievalData ScienceComputational LinguisticsLanguage StudiesContent AnalysisSocial Medium MiningToday MillionsOpinion MiningKnowledge DiscoveryDimensionality ReductionSemantic NetworkSocial Medium DataLinguisticsOpinion Aggregation
Today millions of web-users express their opinions about many topics through blogs, wikis, fora, chats and social networks. For sectors such as e-commerce and e-tourism, it is very useful to automatically analyze the huge amount of social information available on the Web, but the extremely unstructured nature of these contents makes it a difficult task. SenticNet is a publicly available resource for opinion mining built exploiting AI and Semantic Web techniques. It uses dimensionality reduction to infer the polarity of common sense concepts and hence provide a public resource for mining opinions from natural language text at a semantic, rather than just syntactic, level.
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