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Sentiment Polarity Classification at EVALITA: Lessons Learned and Open Challenges
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Overview of the Evalita 2016 Sentiment Polarity Classification Task
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Abstract:
The SENTIment POLarity Classification Task 2016 (SENTIPOLC), is a rerun of the shared task on sentiment classification at the message level on Italian tweets proposed for the first time in 2014 for the Evalita evaluation campaign. It includes three subtasks: subjectivity classification, polarity classification, and irony detection. In 2016 SENTIPOLC has been again the most participated EVALITA task with a total of 57 submitted runs from 13 different teams. We present the datasets – which includes an enriched annotation scheme for dealing with the impact on polarity of a figurative use of language – the evaluation methodology, and discuss results and participating systems.
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Keyword:
Evaluation campaign; Irony Detection; Natural Language Processing; Sentiment analysis; Twitter
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URL: http://ceur-ws.org/Vol-1749/paper_026.pdf http://hdl.handle.net/2318/1644412
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