An approach to detect polarity variation rules for sentiment analysis (Contributo in atti di convegno)

Type
Label
  • An approach to detect polarity variation rules for sentiment analysis (Contributo in atti di convegno) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Alternative label
  • Sangiorgi, Pierluca; Augello, Agnese; Pilato, Giovanni (2014)
    An approach to detect polarity variation rules for sentiment analysis
    in WEBIST 2014
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Sangiorgi, Pierluca; Augello, Agnese; Pilato, Giovanni (literal)
Pagina inizio
  • 344 (literal)
Pagina fine
  • 349 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.scopus.com/record/display.url?eid=2-s2.0-84902376112&origin=inward (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 2 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
  • 2 (literal)
Note
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • ICAR, INAF Istituto di Astrofisica Spaziale e Fisica Cosmica di Palermo (literal)
Titolo
  • An approach to detect polarity variation rules for sentiment analysis (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 9789897580246 (literal)
Abstract
  • Sentiment Analysis is a discipline that aims at identifying and extract the subjectivity expressed by authors of information sources. Sentiment Analysis can be applied at different level of granularity and each of them still has open issues. In this paper we propose a completely unsupervised approach aimed at inducing a set of words patterns that change the polarity of subjective terms. This is a very important task because, while sentiment lexicons are valid tools that can be used to identify the polarity at word level, working at different level of granularity they are no longer sufficient, because of the various aspects to consider like the context, the use of negations and so on that can change the polarity of subjective terms. (literal)
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