Evidence map›Paper›PMID 40880538›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Sociohydrodynamics: Data-driven modeling of social behavior.

Daniel S Seara, Jonathan Colen, Michel Fruchart, Yael Avni, David G Martin, Vincenzo Vitelli

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Sociohydrodynamics: Data-driven modeling of social behavior.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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.

Daniel S SearaJames Franck Institute, University of Chicago, Chicago, IL 60637.ORCID 0000-0001-5615-2888
Jonathan ColenJames Franck Institute, University of Chicago, Chicago, IL 60637.ORCID 0000-0003-4162-0276
Michel FruchartJames Franck Institute, University of Chicago, Chicago, IL 60637.
Yael AvniJames Franck Institute, University of Chicago, Chicago, IL 60637.
David G MartinLeinweber Institute for Theoretical Physics, University of Chicago, Chicago, IL 60637.ORCID 0000-0003-1817-3391
Vincenzo VitelliJames Franck Institute, University of Chicago, Chicago, IL 60637.ORCID 0000-0001-6328-8783

Funding

DOD | USA | AFC | CCDC | Army Research Office (ARO) W911NF-22-2-0109DOD | USA | AFC | CCDC | Army Research Office (ARO) W911NF-23-1-0212National Science Foundation (NSF) 2317138National Science Foundation (NSF) DMR-2011864National Science Foundation (NSF) DMR-2118415
6 · The paper itself

Abstract

Living systems display complex behaviors driven by physical forces as well as decision-making. Hydrodynamic theories hold promise for simplified universal descriptions of socially generated collective behaviors. However, the construction of such theories is often divorced from the data they should describe. Here, we develop and apply a data-driven pipeline that links micromotives to macrobehavior by augmenting hydrodynamics with individual preferences that guide motion. We illustrate this pipeline on a case study of residential dynamics in the United States, for which census and sociological data are available. Guided by Census data, sociological surveys, and neural network analysis, we systematically assess standard hydrodynamic assumptions to construct a sociohydrodynamic model. Solving our minimal hydrodynamic model, calibrated using statistical inference, qualitatively captures key features of residential dynamics at the level of individual US counties. We highlight that a social memory, akin to hysteresis in magnets, emerges in the segregation-integration transition even with memory-less agents. While residential segregation is a multifactorial phenomenon, this physics analogy suggests a simple mechanistic explanation for the phenomenon of neighborhood tipping, whereby a small change in a neighborhood's population leads to a rapid demographic shift. Beyond residential segregation, our work paves the way for systematic investigations of decision-guided motility in real space, from micro-organisms to humans, as well as fitness-mediated motion in more abstract spaces.

Indexed as

HydrodynamicsModels, TheoreticalSocial BehaviorHumansPopulation DynamicsResidence CharacteristicsUnited Statesactive mattereconomicshydrodynamicsmachine learningsociology

Identifiers

PMID40880538
PMCPMC12415204

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.