A minimalistic model of bias, polarization and misinformation in social networks.

ABSTRACT: Online social networks provide users with unprecedented opportunities to engage with diverse opinions. At the same time, they enable confirmation bias on large scales by empowering individuals to self-select narratives they want to be exposed to. A precise understanding of such tradeoffs is still largely missing. We introduce a social learning model where most participants in a network update their beliefs unbiasedly based on new information, while a minority of participants reject information that is incongruent with their preexisting beliefs. This simple mechanism generates permanent opinion polarization and cascade dynamics, and accounts for the aforementioned tradeoff between confirmation bias and social connectivity through analytic results. We investigate the model's predictions empi

SUBMITTER: Sikder O 

PROVIDER: S-EPMC7099021 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature