SenticNet: A publicly available semantic resource for opinion mining

Cambria, Erik; Speer, Robyn; Havasi, Catherine; Hussain, Amir

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.

• Presentation Conference Type: Conference Paper (Published)
• Conference Name: AAAI Fall Symposium
• Start Date: Nov 11, 2010
• End Date: Nov 13, 2010
• Publication Date: 2010
• Deposit Date: Sep 19, 2019
• Volume: FS-10-02
• Pages: 14-18
• Book Title: Commonsense knowledge: Papers from the AAAI Fall Symposium
• ISBN: 978-1-57735-484-0
• Keywords: opinion mining; semantic web; AI
• Public URL: http://researchrepository.napier.ac.uk/Output/1793456