Dataset Information

Modeling confirmation bias and polarization.

ABSTRACT: Online users tend to select claims that adhere to their system of beliefs and to ignore dissenting information. Confirmation bias, indeed, plays a pivotal role in viral phenomena. Furthermore, the wide availability of content on the web fosters the aggregation of likeminded people where debates tend to enforce group polarization. Such a configuration might alter the public debate and thus the formation of the public opinion. In this paper we provide a mathematical model to study online social debates and the related polarization dynamics. We assume the basic updating rule of the Bounded Confidence Model (BCM) and we develop two variations a) the Rewire with Bounded Confidence Model (RBCM), in which discordant links are broken until convergence is reached; and b) the Unbounded Confidence Model, under which the interaction among discordant pairs of users is allowed even with a negative feedback, either with the rewiring step (RUCM) or without it (UCM). From numerical simulations we find that the new models (UCM and RUCM), unlike the BCM, are able to explain the coexistence of two stable final opinions, often observed in reality. Lastly, we present a mean field approximation of the newly introduced models.

SUBMITTER: Del Vicario M

PROVIDER: S-EPMC5225437 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Modeling confirmation bias and polarization.

Del Vicario Michela M Scala Antonio A Caldarelli Guido G Stanley H Eugene HE Quattrociocchi Walter W

Scientific reports 20170111

Online users tend to select claims that adhere to their system of beliefs and to ignore dissenting information. Confirmation bias, indeed, plays a pivotal role in viral phenomena. Furthermore, the wide availability of content on the web fosters the aggregation of likeminded people where debates tend to enforce group polarization. Such a configuration might alter the public debate and thus the formation of the public opinion. In this paper we provide a mathematical model to study online social de ...[more]

PMID: 28074874

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Project description:The goal of this experimental project was to investigate lay peoples' perceptions of epistemic authority (EA) in the field of finance. EA is defined as the extent to which a source of information is treated as evidence for judgments independently of its objective expertise and based on subjective beliefs. Previous research suggested that EA evaluations are biased and that lay people tend to ascribe higher EA to experts who advise action (in the case of medical experts) or confirm clients' expectations (in the case of politicians). However, there has been no research into biases in lay evaluations of financial experts and this project is aimed to fill this gap. Experiment 1 showed that lay people tended to ascribe greater authority to financial consultants who gave more active advice to clients considering taking out a mortgage. Experiment 2 confirmed the action advice effect found in Experiment 1. However, the outcomes of Experiments 2 and - particularly - 3 suggested that this bias might also be due to clients' desire to confirm their own opinions. Experiment 2 showed that the action advice effect was moderated by clients' own opinions on taking loans. Lay people ascribed the greatest EA to the advisor in the scenario in which he advised taking action and where this coincided with the client's positive opinion on the advisability of taking out a loan. In Experiment 3 only participants with a positive opinion on the financial product ascribed greater authority to experts who recommended it; participants whose opinion was negative tended to rate consultants who advised rejecting the product more highly. To conclude, these three experiments revealed that lay people ascribe higher EA to financial consultants who advise action rather than maintenance of the status quo, but this effect is limited by confirmation bias: when the client's a priori opinion is salient, greater authority is ascribed to experts whose advice confirms it. In this sense, results presented in the present paper suggest that the action advice effect might be also interpreted as a specific manifestation of confirmation bias.

Dataset Information

Modeling confirmation bias and polarization.

Publications

Modeling confirmation bias and polarization.

Similar Datasets

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