Confirmation bias in social networks
نویسندگان
چکیده
In this study, I present a theoretical social learning model to investigate how confirmation bias affects opinions when agents exchange information over network. Hence, besides exchanging with friends, observe public sequence of potentially ambiguous signals and interpret it according rule that includes bias. First, study shows regardless level ambiguity both for people or networked society, only two types can be formed, are biased. However, one opinion type is less biased than the other depending on state world. The size biases depends relative magnitude biases. long-run not attained even impartially ambiguity. Finally, analytically confirming probability emergence less-biased consensus connected have different priors difficult. used simulations analyze its determinants found three main results: (i) some network topologies more conducive efficiency, (ii) degree partisanship enhances efficiency under (iii) open-mindedness (i.e. partisans agree opposing partisans) might inhibit in cases.
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ژورنال
عنوان ژورنال: Mathematical Social Sciences
سال: 2023
ISSN: ['1879-3118', '0165-4896']
DOI: https://doi.org/10.1016/j.mathsocsci.2023.02.007