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Poster Communications Year : 2014

Using Fuzzy Logic For Multi-Domain Sentiment Analysis


Recent advances in the Sentiment Analysis field focus on the inves-tigation about the polarities that concepts describing the same sentiment have when they are used in different domains. In this paper, we investigated on the use of fuzzy logic representation for modeling knowledge concerning the relation-ships between sentiment concepts and different domains. The developed system is built on top of a knowledge base defined by integrating WordNet and SenticNet, and it implements an algorithm used for learning the use of sentiment concepts from multi-domain datasets and for propagating such information to each con-cept of the knowledge base. The system has been validated on the Blitzer dataset, a multi-domain sentiment dataset built by using reviews of Amazon products, by demonstrating the effectiveness of the proposed approach.
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hal-01078205 , version 1 (28-10-2014)


  • HAL Id : hal-01078205 , version 1


Mauro Dragoni, Andrea G. B. Tettamanzi, Célia da Costa Pereira. Using Fuzzy Logic For Multi-Domain Sentiment Analysis. Matthew Horridge; Marco Rospocher; Jacco van Ossenbruggen. ISWC 2014 Posters & Demonstrations Track, Oct 2014, Riva del Garda (TN), Italy. Sun SITE Central Europe (CEUR), CEUR Workshop Preoceedings, 1272, pp.305 - 308, 2014, ISWC 2014 Posters & Demonstrations Track, Riva del Garda, Italy, October 21, 2014. ⟨hal-01078205⟩
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