SenticNet: A publicly available semantic resource for opinion mining

Citation

Cambria E, Speer R, Havasi C & Hussain A (2010) SenticNet: A publicly available semantic resource for opinion mining. In: Commonsense Knowledge: Papers from the AAAI Fall Symposium. Fall Symposium Series Technical Reports, FS-10-02. 2010 AAAI Fall Symposium, Arlington, VA, USA, 11.11.2010-13.11.2010. Menlo Park, CA, USA: AAAI Press, pp. 14-18. http://www.aaai.org/Press/Reports/Symposia/Fall/fall-reports.php

Abstract
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.

Keywords
AI; Semantic Web; Opinion Mining