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Conference on Artificial Intelligence and Natural Language

AINL 2018: Artificial Intelligence and Natural Language pp 197–209Cite as

Modeling Propaganda Battle: Decision-Making, Homophily, and Echo Chambers

Part of the Communications in Computer and Information Science book series (CCIS,volume 930)

Abstract

Studies concerning social patterns that appear as a result of propaganda and rumors generally tend to neglect considerations of the behavior of individuals that constitute these patterns. This places obvious limitations upon the scope of research. We propose a dynamical model for the mechanics of the processes of polarization and formation of echo chambers. This model is based on the Rashevsky neurological scheme of decision-making.

Keywords

  • Social homophily
  • Polarization
  • Selective exposure
  • Echo chambers
  • Decision-making
  • Rashevsky’s neurological scheme
  • Rumors

Supported by the Russian Foundation for Basic Research (project 17-01-00390 A).

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Author information

Authors and Affiliations

  1. Keldysh Institute of Applied Mathematics, Moscow, Russia

    Alexander Petrov & Olga Proncheva

  2. Moscow Institute of Physics and Technology, Dolgoprudny, Russia

    Olga Proncheva

Authors
  1. Alexander Petrov
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  2. Olga Proncheva
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Corresponding author

Correspondence to Olga Proncheva .

Editor information

Editors and Affiliations

  1. Data and Web Science Group, University of Mannheim, Mannheim, Baden-Württemberg, Germany

    Dmitry Ustalov

  2. ITMO University, St. Petersburg, Russia

    Andrey Filchenkov

  3. University of Helsinki, Helsinki, Finland

    Lidia Pivovarova

  4. Mendel University, Brno, Czech Republic

    Jan Žižka

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Petrov, A., Proncheva, O. (2018). Modeling Propaganda Battle: Decision-Making, Homophily, and Echo Chambers. In: Ustalov, D., Filchenkov, A., Pivovarova, L., Žižka, J. (eds) Artificial Intelligence and Natural Language. AINL 2018. Communications in Computer and Information Science, vol 930. Springer, Cham. https://doi.org/10.1007/978-3-030-01204-5_19

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  • DOI: https://doi.org/10.1007/978-3-030-01204-5_19

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