Article
Details
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
Status | Published |
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Publication date | 31/03/2013 |
URL | |
Publisher | IEEE |
ISSN | 1541-1672 |