This paper describes the CoLing Lab system for the EVALITA 2014 SENTIment POLarity Classification (SENTIPOLC) task. Our system is based on a SVM classifier trained on the rich set of lexical, global and twitter-specific features described in these pages. Overall, our system reached a 0.63 weighted F-score on the test set provided by the task organizers.

The CoLing Lab system for Sentiment Polarity Classification of tweets

Lebani Gianluca;
2014

Abstract

This paper describes the CoLing Lab system for the EVALITA 2014 SENTIment POLarity Classification (SENTIPOLC) task. Our system is based on a SVM classifier trained on the rich set of lexical, global and twitter-specific features described in these pages. Overall, our system reached a 0.63 weighted F-score on the test set provided by the task organizers.
Proceedings of the Fourth International Workshop EVALITA 2014
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10278/3715955
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