Evidence map›Paper›PMID 41238602›Full record

ArticleScientific reports2025

Self-organizing group structure through rewiring for collective decision-making in evolving environments.

Poong Oh, Andrew Schauf

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Poong OhWee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore, 639798, Singapore. poongoh@ntu.edu.sg.
Andrew SchaufCenter for Transdisciplinary and Sustainability Sciences, IPB University, Bogor, Jawa Barat, 16127, Indonesia.

Funding

Ministry of Education - Singapore 022240-00001
6 · The paper itself

Abstract

DeGroot dynamics, a prototypical model of opinion formation under social influence, tends to yield biased consensus in centralized groups. However, such a consensus can be accurate if competent individuals occupy central positions and exert disproportionate influence. Focusing on groups with stable memberships that engage in iterative consensus formation across a sequence of issues, we propose social network rewiring as a self-organization mechanism that identifies competent members and positions them centrally, thereby empowering them to make decisions on behalf of the group. Numerical experiments show that the effects of rewiring on consensus accuracy and structural adaptability oppose each other depending on its search scope. Local rewiring-where agents search for new connections within their immediate neighborhoods-progressively concentrates influence among competent members and enhances consensus accuracy but reduces the group's adaptability to evolving environments, modeled as temporal shifts in individual competence. In contrast, global rewiring-where agents may connect to any member of the group-preserves adaptability but significantly undermines accuracy. A unique contribution of this study lies in its novel approach to information integration for collective decision-making, shifting the focus from the intrinsic information individuals possess to information about agents' competence, acquired from local interactions and communicated through rewiring.

Indexed as

Decision MakingGroup StructureSocial NetworkingConsensusHumansModels, PsychologicalPeer InfluenceCollective decision-makingCompetence-based hierarchyDeGroot dynamicsEvolving environmentInformation integrationNetwork rewiring

Identifiers

PMID41238602
PMCPMC12618610

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.