ArticleProceedings of the National Academy of Sciences of the United States of America2020
Adaptive social networks promote the wisdom of crowds.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
What it found
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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.
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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.
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Who cites it
42 citing papers in PubMed.
- Payoff selectivity drives collective intelligence during dynamic resource tracking in humans.Nature communications · 2026Article
- Optimal interventions to curb urban conflagration.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Conformity to popular, not average, opinions: Models, data, and evolution.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- One's Actions "Aging Poorly": An Integrative Egocentric Framework for Understanding Impression Management Errors and the Challenge of Temporal Impression Management.Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc · 2026Review
- An ensemble method utilising multiple thinking styles that boosts the wisdom-of inner- crowd effect.Scientific reports · 2025Article
- Perceived legitimacy of layperson and expert content moderators.PNAS nexus · 2025Article
- Mixing individual and collective behaviors to predict out-of-routine mobility.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Conformity to continuous and discrete ordered traits.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- Collective dynamics behind success.Nature communications · 2024Review
- AI-enhanced collective intelligence.Patterns (New York, N.Y.) · 2024Review
- Article
- The power of sound: unravelling how acoustic communication shapes group dynamics.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- The functional aspects of selective exposure for collective decision-making under social influence.Scientific reports · 2024Article
- Network structure shapes the impact of diversity in collective learning.Scientific reports · 2024Article
- Interaction among participants in a collective intelligence experiment: an emotional approach.Frontiers in psychology · 2024Article
- Multidisciplinary learning through collective performance favors decentralization.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Experimental evidence for structured information-sharing networks reducing medical errors.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Humans strategically avoid connecting to others who agree and avert the emergence of network polarization in a coordination task.Scientific reports · 2023Article
- Beyond collective intelligence: Collective adaptation.Journal of the Royal Society, Interface · 2023Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Social networks continuously change as new ties are created and existing ones fade. It is widely acknowledged that our social embedding has a substantial impact on what information we receive and how we form beliefs and make decisions. However, most empirical studies on the role of social networks in collective intelligence have overlooked the dynamic nature of social networks and its role in fostering adaptive collective intelligence. Therefore, little is known about how groups of individuals dynamically modify their local connections and, accordingly, the topology of the network of interactions to respond to changing environmental conditions. In this paper, we address this question through a series of behavioral experiments and supporting simulations. Our results reveal that, in the presence of plasticity and feedback, social networks can adapt to biased and changing information environments and produce collective estimates that are more accurate than their best-performing member. To explain these results, we explore two mechanisms: 1) a global-adaptation mechanism where the structural connectivity of the network itself changes such that it amplifies the estimates of high-performing members within the group (i.e., the network "edges" encode the computation); and 2) a local-adaptation mechanism where accurate individuals are more resistant to social influence (i.e., adjustments to the attributes of the "node" in the network); therefore, their initial belief is disproportionately weighted in the collective estimate. Our findings substantiate the role of social-network plasticity and feedback as key adaptive mechanisms for refining individual and collective judgments.
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Registered trials
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.