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Enhanced SenticNet with Affective Labels for Concept-Based Opinion Mining
Found in: IEEE Intelligent Systems
By Soujanya Poria,Alexander Gelbukh,Amir Hussain,Newton Howard,Dipankar Das,Sivaji Bandyopadhyay
Issue Date:March 2013
pp. 31-38
SenticNet 1.0 is one of the most widely used, publicly available resources for concept-based opinion mining. The presented methodology enriches SenticNet concepts with affective information by assigning an emotion label.
Enriching SenticNet Polarity Scores through Semi-Supervised Fuzzy Clustering
Found in: 2012 IEEE 12th International Conference on Data Mining Workshops
By Soujanya Poria,Alexander Gelbukh,Erik Cambria,Dipankar Das,Sivaji Bandyopadhyay
Issue Date:December 2012
pp. 709-716
SenticNet 1.0 is one of the most widely used freely-available resources for concept-level opinion mining, containing about 5,700 common sense concepts and their corresponding polarity scores. Specific affective information associated to such concepts, howe...