Synalp-Empathic: A Valence Shifting Hybrid System for Sentiment Analysis

Alexandre Denis (1) , Samuel Cruz-Lara (1) , Nadia Bellalem (1) , Lotfi Bellalem (1)

1 SYNALP - Natural Language Processing : representations, inference and semantics

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]

Alexandre Denis, Samuel Cruz-Lara, Nadia Bellalem, Lotfi Bellalem. Synalp-Empathic: A Valence Shifting Hybrid System for Sentiment Analysis. 8th International Workshop on Semantic Evaluation (SemEval 2014), Aug 2014, Dublin, Ireland. pp.605 - 609. ⟨hal-01099671⟩