Enhanced SenticNet with affective labels for concept-based opinion mining

Citation

Poria S, Gelbukh A, Hussain A, Howard N, Das D & Bandyopadhyay S (2013) Enhanced SenticNet with affective labels for concept-based opinion mining. IEEE Intelligent Systems, 28 (2), pp. 31-38. https://doi.org/10.1109/MIS.2013.4

Abstract
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.

Journal
IEEE Intelligent Systems: Volume 28, Issue 2