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Modelling Spirals of Silence and Echo Chambers by Learning from the Feedback of Others

What are the mechanisms by which groups with certain opinions gain public voice and force others holding a different view into silence? Furthermore, how does social media play into this? Drawing on neuroscientific insights into the processing of social feedback, we develop a theoretical model that a...

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Detalles Bibliográficos
Autores principales: Banisch, Sven, Gaisbauer, Felix, Olbrich, Eckehard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9601760/
https://www.ncbi.nlm.nih.gov/pubmed/37420504
http://dx.doi.org/10.3390/e24101484
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author Banisch, Sven
Gaisbauer, Felix
Olbrich, Eckehard
author_facet Banisch, Sven
Gaisbauer, Felix
Olbrich, Eckehard
author_sort Banisch, Sven
collection PubMed
description What are the mechanisms by which groups with certain opinions gain public voice and force others holding a different view into silence? Furthermore, how does social media play into this? Drawing on neuroscientific insights into the processing of social feedback, we develop a theoretical model that allows us to address these questions. In repeated interactions, individuals learn whether their opinion meets public approval and refrain from expressing their standpoint if it is socially sanctioned. In a social network sorted around opinions, an agent forms a distorted impression of public opinion enforced by the communicative activity of the different camps. Even strong majorities can be forced into silence if a minority acts as a cohesive whole. On the other hand, the strong social organisation around opinions enabled by digital platforms favours collective regimes in which opposing voices are expressed and compete for primacy in public. This paper highlights the role that the basic mechanisms of social information processing play in massive computer-mediated interactions on opinions.
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spelling pubmed-96017602022-10-27 Modelling Spirals of Silence and Echo Chambers by Learning from the Feedback of Others Banisch, Sven Gaisbauer, Felix Olbrich, Eckehard Entropy (Basel) Article What are the mechanisms by which groups with certain opinions gain public voice and force others holding a different view into silence? Furthermore, how does social media play into this? Drawing on neuroscientific insights into the processing of social feedback, we develop a theoretical model that allows us to address these questions. In repeated interactions, individuals learn whether their opinion meets public approval and refrain from expressing their standpoint if it is socially sanctioned. In a social network sorted around opinions, an agent forms a distorted impression of public opinion enforced by the communicative activity of the different camps. Even strong majorities can be forced into silence if a minority acts as a cohesive whole. On the other hand, the strong social organisation around opinions enabled by digital platforms favours collective regimes in which opposing voices are expressed and compete for primacy in public. This paper highlights the role that the basic mechanisms of social information processing play in massive computer-mediated interactions on opinions. MDPI 2022-10-18 /pmc/articles/PMC9601760/ /pubmed/37420504 http://dx.doi.org/10.3390/e24101484 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Banisch, Sven
Gaisbauer, Felix
Olbrich, Eckehard
Modelling Spirals of Silence and Echo Chambers by Learning from the Feedback of Others
title Modelling Spirals of Silence and Echo Chambers by Learning from the Feedback of Others
title_full Modelling Spirals of Silence and Echo Chambers by Learning from the Feedback of Others
title_fullStr Modelling Spirals of Silence and Echo Chambers by Learning from the Feedback of Others
title_full_unstemmed Modelling Spirals of Silence and Echo Chambers by Learning from the Feedback of Others
title_short Modelling Spirals of Silence and Echo Chambers by Learning from the Feedback of Others
title_sort modelling spirals of silence and echo chambers by learning from the feedback of others
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9601760/
https://www.ncbi.nlm.nih.gov/pubmed/37420504
http://dx.doi.org/10.3390/e24101484
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