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

Sven BanischFelix GaisbauerEckehard Olbrich
Published in: Entropy (Basel, Switzerland) (2022)
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.
Keyphrases
  • healthcare
  • mental health
  • social media
  • health information
  • magnetic resonance
  • deep learning