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Opinion amplification causes extreme polarization in social networks.
Lim, Soo Ling; Bentley, Peter J.
Afiliação
  • Lim SL; Department of Computer Science, University College London, London, UK. s.lim@cs.ucl.ac.uk.
  • Bentley PJ; Department of Computer Science, University College London, London, UK.
Sci Rep ; 12(1): 18131, 2022 10 28.
Article em En | MEDLINE | ID: mdl-36307510
ABSTRACT
Extreme polarization of opinions fuels many of the problems facing our societies today, from issues on human rights to the environment. Social media provides the vehicle for these opinions and enables the spread of ideas faster than ever before. Previous computational models have suggested that significant external events can induce extreme polarization. We introduce the Social Opinion Amplification Model (SOAM) to investigate an alternative

hypothesis:

that opinion amplification can result in extreme polarization. SOAM models effects such as sensationalism, hype, or "fake news" as people express amplified versions of their actual opinions, motivated by the desire to gain a greater following. We show for the first time that this simple idea results in extreme polarization, especially when the degree of amplification is small. We further show that such extreme polarization can be prevented by two

methods:

preventing individuals from amplifying more than five times, or through consistent dissemination of balanced opinions to the population. It is natural to try and have the loudest voice in a crowd when we seek attention; this work suggests that instead of shouting to be heard and generating an uproar, it is better for all if we speak with moderation.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Rede Social / Mídias Sociais Tipo de estudo: Etiology_studies Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Rede Social / Mídias Sociais Tipo de estudo: Etiology_studies Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Reino Unido