Evidence map›Paper›PMID 28074874›Full record

ArticleScientific reports2017

Modeling confirmation bias and polarization.

Michela Del Vicario, Antonio Scala, Guido Caldarelli, H Eugene Stanley, Walter Quattrociocchi

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

47 citing papers in PubMed.

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  10. Effects of dehumanization and disgust-eliciting language on attitudes toward immigration: a sentiment analysis of Twitter data.Psychiatry, psychology, and law : an interdisciplinary journal of the Australian and New Zealand Association of Psychiatry, Psychology and Law · 2025
    Article
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  16. The roots of polarization in the individual reward system.Proceedings. Biological sciences · 2024
    Article
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  18. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Michela Del VicarioLaboratory of Computational Social Science, Networks Dept, IMT School for Advanced Studies, 55100 Lucca, Italy.
Antonio ScalaLaboratory of Computational Social Science, Networks Dept, IMT School for Advanced Studies, 55100 Lucca, Italy.
Guido CaldarelliLaboratory of Computational Social Science, Networks Dept, IMT School for Advanced Studies, 55100 Lucca, Italy.
H Eugene StanleyBoston University, Center for Polymer Studies, Department of Physics, Boston, Massachusetts 02215, USA.
Walter QuattrociocchiLaboratory of Computational Social Science, Networks Dept, IMT School for Advanced Studies, 55100 Lucca, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

BiasModels, TheoreticalComputer SimulationMonte Carlo MethodProbability

Identifiers

PMID28074874
PMCPMC5225437

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.