Evidence map›Paper›PMID 33398148›Full record

ArticleNature human behaviour2021

Evolutionary dynamics of higher-order interactions in social networks.

Unai Alvarez-Rodriguez, Federico Battiston, Guilherme Ferraz de Arruda, Yamir Moreno, Matjaž Perc, Vito Latora

Abstract read
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In one paragraph

Article in Nature human behaviour, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing 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

68 citing papers in PubMed.

  1. Article
  2. Article
  3. Hyperedge approximation for stochastic processes on higher-order networks.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  4. Article
  5. Article
  6. On the optimal integration of intelligent agents into network systems to steer cooperation.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  7. Article
  8. Article
  9. Strategy evolution on temporal hypergraphs.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Promoting collective cooperation through temporal interactions.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article

8 more citing papers are in PubMed but not listed here.

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

6 authors.

Unai Alvarez-RodriguezBasque Centre for Climate Change (BC3), Leioa, Spain. unaialvarezr@gmail.com.ORCID http://orcid.org/0000-0003-4962-9777
Federico BattistonDepartment of Network and Data Science, Central European University, Vienna, Austria.ORCID http://orcid.org/0000-0001-9646-6232
Guilherme Ferraz de ArrudaISI Foundation, Turin, Italy.ORCID http://orcid.org/0000-0003-1647-5126
Yamir MorenoISI Foundation, Turin, Italy.ORCID http://orcid.org/0000-0002-0895-1893
Matjaž PercFaculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia.ORCID http://orcid.org/0000-0002-3087-541X
Vito LatoraSchool of Mathematical Sciences, Queen Mary University of London, London, UK.ORCID http://orcid.org/0000-0002-0984-8038

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We live and cooperate in networks. However, links in networks only allow for pairwise interactions, thus making the framework suitable for dyadic games, but not for games that are played in larger groups. Here, we study the evolutionary dynamics of a public goods game in social systems with higher-order interactions. First, we show that the game on uniform hypergraphs corresponds to the replicator dynamics in the well-mixed limit, providing a formal theoretical foundation to study cooperation in networked groups. Second, we unveil how the presence of hubs and the coexistence of interactions in groups of different sizes affects the evolution of cooperation. Finally, we apply the proposed framework to extract the actual dependence of the synergy factor on the size of a group from real-world collaboration data in science and technology. Our work provides a way to implement informed actions to boost cooperation in social groups.

Indexed as

Cooperative BehaviorModels, TheoreticalSocial NetworkingHumans

Identifiers

What OpenQuestion holds

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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.