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Beyond Fact-Checking: Network Analysis Tools for Monitoring Disinformation in Social Media

Part of the Studies in Computational Intelligence book series (SCI,volume 881)

Abstract

Operated by the H2020 SOMA Project, the recently established Social Observatory for Disinformation and Social Media Analysis supports researchers, journalists and fact-checkers in their quest for quality information. At the core of the Observatory lies the DisInfoNet Toolbox, designed to help a wide spectrum of users understand the dynamics of (fake) news dissemination in social networks. DisInfoNet combines text mining and classification with graph analysis and visualization to offer a comprehensive and user-friendly suite. To demonstrate the potential of our Toolbox, we consider a Twitter dataset of more than 1.3M tweets focused on the Italian 2016 constitutional referendum and use DisInfoNet to: (i) track relevant news stories and reconstruct their prevalence over time and space; (ii) detect central debating communities and capture their distinctive polarization/narrative; (iii) identify influencers both globally and in specific “disinformation networks”.

Keywords

  • Social network analysis
  • Disinformation
  • Classification

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Notes

  1. 1.

    https://www.truly.media/.

  2. 2.

    Please, contact the authors if you wish to be notified when the code is released.

  3. 3.

    https://app.truthnest.com/.

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Correspondence to Stefano Guarino .

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Guarino, S., Trino, N., Chessa, A., Riotta, G. (2020). Beyond Fact-Checking: Network Analysis Tools for Monitoring Disinformation in Social Media. In: Cherifi, H., Gaito, S., Mendes, J., Moro, E., Rocha, L. (eds) Complex Networks and Their Applications VIII. COMPLEX NETWORKS 2019. Studies in Computational Intelligence, vol 881. Springer, Cham. https://doi.org/10.1007/978-3-030-36687-2_36

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