SenticNet: A Publicly Available Semantic Resource for Opinion Mining

Cambria, Erik (University of Stirling) | Speer, Robyn (Massachusetts Institute of Technology) | Havasi, Catherine (Massachusetts Institute of Technology) | Hussain, Amir (University of Stirling)

AAAI Conferences 

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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