SenticNet is a publicly available semantic and affective resource for concept-level opinion mining and sentiment analysis. Rather than using graph-mining and dimensionality-reduction techniques, SenticNet 3 makes use of 'energy flows' to connect various parts of extended common and common-sense knowledge representations to one another. SenticNet 3 models nuanced semantics and sentics (that is, the conceptual and affective information associated with multi-word natural language expressions), representing information with a symbolic opacity intermediate between that of neural networks and of typical symbolic systems.
CITATION STYLE
Cambria, E., Olsher, D., & Kwok, K. (2014). SenticNet 3: A Common and Common-Sense Knowledge Base for Cognition-Driven Sentiment Analysis. In Proceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014 (pp. 1988–1995). The Cognitive Science Society. https://doi.org/10.1609/aaai.v28i1.8928
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