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
PASSARO, LUCIA;LEBANI, GIANLUCA;Pollacci, Laura;LENCI, ALESSANDRO
2014-01-01
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.File in questo prodotto:
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CoLingLab_SentiPolc14.pdf
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