The CoLing Lab system for Sentiment Polarity Classification of tweets

Passaro, Lucia C. and Lebani, Gianluca E. and Pollaci, Laura and Chersoni, Emmanuele and Lenci, Alessandro (2014) The CoLing Lab system for Sentiment Polarity Classification of tweets. In: Proceedings of the First Italian Conference on Computational Linguistics CLiC-it 2014 & and of the Fourth International Workshop EVALITA 2014, 9-11 December 2014, Pisa.

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Abstract

SUMMARY. 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. Over all, our system reached a 0.63 weighted F-score on the test set provided by the task organizers. RIASSUNTO. Questo contributo descrive il sistema CoLing Lab sviluppato per il task di SENTIment POLarity Classification (SENTIPOL C) organizzato nel contesto della campagna EVALITA 2014. Il nostro sistema è basato su un classificatore SVM addestrato sulle feature lessicali, globali e specifiche del canale twitter descritte in queste pagine. Il nostro sistema raggiunge uno score di circa 0.63 nel test set fornito dagli organizzatori del task.

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