Synalp-Empathic: A Valence Shifting Hybrid System for Sentiment Analysis
Résumé
This paper describes the Synalp-Empathic system that competed in SemEval-2014 Task 9B Sentiment Analysis in Twitter. Our system combines syntactic-based va-lence shifting rules with a supervised learning algorithm (Sequential Minimal Optimization). We present the system, its features and evaluate their impact. We show that both the valence shifting mech-anism and the supervised model enable to reach good results.
Domaines
Interface homme-machine [cs.HC]| Origine | Fichiers produits par l'(les) auteur(s) |
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