Abstract
An emerging field within Sentiment Analysis concerns the investigation about how sentiment concepts have to be adapted with respect to the different domains in which they are used. In the context of the Concept-Level Sentiment Analysis Challenge, we presented a system whose aims are twofold: (i) the implementation of a learning approach able to model fuzzy functions used for building the relationships graph representing the appropriateness between sentiment concepts and different domains (Task 1); and (ii) the development of a semantic resource based on the connection between an extended version of WordNet, SenticNet, and ConceptNet, that has been used both for extracting concepts (Task 2) and for classifying sentences within specific domains (Task 3).
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Notes
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Detailed results and tool demo are available at http://dkmtools.fbk.eu/moki/demo/mdfsa/mdfsa_demo.html.
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Dragoni, M., Tettamanzi, A.G.B., da Costa Pereira, C. (2014). A Fuzzy System for Concept-Level Sentiment Analysis. In: Presutti, V., et al. Semantic Web Evaluation Challenge. SemWebEval 2014. Communications in Computer and Information Science, vol 475. Springer, Cham. https://doi.org/10.1007/978-3-319-12024-9_2
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