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Similarity Fuzzy Semantic Networks and Inference. An Application to Analysis of Radical Discourse in Twitter

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Artificial Intelligence and Soft Computing (ICAISC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13588))

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Abstract

In this paper we introduce a new Knowledge Representation model, the Similarity Fuzzy Semantic Networks. It is an extension of Fuzzy Semantic Networks that incorporates reasoning by similarity through a Similarity Inference Rule. Moreover, we show as it can be effectively applied to a trending and complex problem like the analysis of radical discourse in Twitter.

This work was financially supported by Junta de Andalucia, projects P18-FR-5020 and A-HUM-250-UGR18, and cofinanced by the European Social Fund (ESF). Manuel Francisco Aparicio was supported by the FPI 2017 predoctoral programme, from the Spanish Ministry of Economy and Competitiveness (MINECO), grant reference BES-2017-081202.

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Authors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, University of Granada, 18071, Granada, Spain

    Juan Luis Castro & Manuel Francisco

Authors
  1. Juan Luis Castro
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  2. Manuel Francisco
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Corresponding author

Correspondence to Manuel Francisco .

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Editors and Affiliations

  1. Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Castro, J.L., Francisco, M. (2023). Similarity Fuzzy Semantic Networks and Inference. An Application to Analysis of Radical Discourse in Twitter. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2022. Lecture Notes in Computer Science(), vol 13588. Springer, Cham. https://doi.org/10.1007/978-3-031-23492-7_15

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  • DOI: https://doi.org/10.1007/978-3-031-23492-7_15

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