Web 2.0 has changed the ways people communicate, collaborate, express their opinions and sentiments. But despite social data on the Web being perfectly suitable for human consumption, they remain hardly accessible to machines. To bridge the cognitive and affective gap between word-level natural language data and the concept-level opinions and sentiments conveyed by them, we are developing SenticNet, a publicly available semantic and affective resource for opinion mining and sentiment analysis, built by means of sentic computing. By providing the semantics and sentics (that is, the cognitive and affective information) associated with over 14,000 concepts, SenticNet represents one of the most comprehensive semantic resources for the development of affect-sensitive applications in fields such as social data mining, multimodal affective HCI and social media marketing.

•  More information about SenticNet can be found here: AAAI CSK-10 paper
•  The first version of SenticNet can be downloaded here: SenticNet-1.0
•  A sample of SenticNet 2, paper to appear in FLAIRS-12, is available at: SenticNet-2.0 sample
•  For SenticNet updates and opinion mining CFPs, please subscribe to feed://sentic.net/feed or follow us on Twitter, LinkedIn, and Facebook.