The IRMUDOSA System at ESWC-2017 Challenge on Semantic Sentiment Analysis

  • Giulio Petrucci
  • Mauro DragoniEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 769)


Multi-Domain opinion mining consists in estimating the polarity of a document by exploiting domain-specific information. One of the main issue of the approaches discussed in literature is their poor capability of being applied on domains that have not been used for building the opinion model. In this paper, we present an approach exploiting the linguistic overlap between domains for building models enabling the estimation of polarities for documents belonging to any other domain. The system implementing such an approach has been presented at the third edition of the Semantic Sentiment Analysis Challenge co-located with ESWC 2017. Fuzzy representation of features polarity supports the modeling of information uncertainty learned from training set and integrated with knowledge extracted from two well-known resources used in the opinion mining field, namely Sentic.Net and the General Inquirer. The proposed technique has been validated on a multi-domain dataset and the results demonstrated the effectiveness of the proposed approach by setting a plausible starting point for future work.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Universitá di TrentoTrentoItaly
  2. 2.Fondazione Bruno KesslerTrentoItaly

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