Synalp-Empathic: A Valence Shifting Hybrid System for Sentiment Analysis
نویسندگان
چکیده
This paper describes the Synalp-Empathic system that competed in SemEval-2014 Task 9B Sentiment Analysis in Twitter. Our system combines syntactic-based valence 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 mechanism and the supervised model enable to reach good results.
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