In recent years computational linguistics has seen a rising interest in subjectivity, opinions, feelings and emotions. Even though great attention has been given to polarity recognition, the research in emotion detection has had to rely on small emotion resources. In this paper, we present a methodology to build emotive lexicons by jointly exploiting vector space models and human annotation, and we provide the first results of the evaluation with a crowdsourcing experiment.

ItEM: A Vector Space Model to Bootstrap an Italian Emotive Lexicon

PASSARO, LUCIA;Pollacci, Laura;LENCI, ALESSANDRO
2015-01-01

Abstract

In recent years computational linguistics has seen a rising interest in subjectivity, opinions, feelings and emotions. Even though great attention has been given to polarity recognition, the research in emotion detection has had to rely on small emotion resources. In this paper, we present a methodology to build emotive lexicons by jointly exploiting vector space models and human annotation, and we provide the first results of the evaluation with a crowdsourcing experiment.
2015
978-88-99200-62-6
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/766226
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