Evidence map›Paper›PMID 38086404›Full record

ArticleJournal of the Royal Society, Interface2023

Social identity bias and communication network clustering interact to shape patterns of opinion dynamics.

Peter Steiglechner, Paul E Smaldino, Deyshawn Moser, Agostino Merico

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
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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

4 authors.

Peter SteiglechnerSystems Ecology Group, Leibniz Centre for Tropical Marine Research (ZMT), Bremen, Germany.ORCID 0000-0002-1937-5983
Paul E SmaldinoDepartment of Cognitive and Information Sciences, University of California Merced, Merced, CA, USA.ORCID 0000-0002-7133-5620
Deyshawn MoserInstitutional and Behavioural Economics Group, Leibniz Centre for Tropical Marine Research (ZMT), Bremen, Germany.ORCID 0000-0003-1789-9393
Agostino MericoSystems Ecology Group, Leibniz Centre for Tropical Marine Research (ZMT), Bremen, Germany.ORCID 0000-0001-8095-8056

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Social influence aligns people's opinions, but social identities and related in-group biases interfere with this alignment. For instance, the recent rise of young climate activists (e.g. 'Fridays for Future' or 'Last Generation') has highlighted the importance of generational identities in the climate change debate. It is unclear how social identities affect the emergence of opinion patterns, such as consensus or disagreement, in a society. Here, we present an agent-based model to explore this question. Agents communicate in a network and form opinions through social influence. The agents have fixed social identities which involve homophily in their interaction preferences and in-group bias in their perception of others. We find that the in-group bias has opposing effects depending on the network topology. The bias impedes consensus in highly random networks by promoting the formation of echo chambers within social identity groups. By contrast, the bias facilitates consensus in highly clustered networks by aligning dispersed in-group agents across the network and, thereby, preventing the formation of isolated echo chambers. Our model uncovers the mechanisms underpinning these opposing effects of the in-group bias and highlights the importance of the communication network topology for shaping opinion dynamics.

Indexed as

AttitudeSocial IdentificationBiasClimate ChangeConsensusHumansagent-based modelclimate changecomputational social sciencegenerational conflictin-group biasopinion dynamics

Identifiers

PMID38086404
PMCPMC10715916

What OpenQuestion holds

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LicenceCC BY
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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.