Exercise contagion in a global social network
Open accessAbstract
We leveraged exogenous variation in weather patterns across geographies to identify social contagion in exercise behaviours across a global social network. We estimated these contagion effects by combining daily global weather data, which creates exogenous variation in running among friends, with data on the network ties and daily exercise patterns of ∼1.1M individuals who ran over 350M km in a global social network over 5 years. Here we show that exercise is socially contagious and that its contagiousness varies with the relative activity of and gender relationships between friends. Less active runners influence more active runners, but not the reverse. Both men and women influence men, while only women influence other women. While the Embeddedness and Structural Diversity theories of social contagion explain the influence effects we observe, the Complex Contagion theory does not. These results suggest interventions that account for social contagion will spread behaviour change more effectively.
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An analysis of exercise patterns in a global social network of 1.1 million runners demonstrated that exercise is 'contagious', whose effect depends on gender and relative levels of activity.
“Another analysis of exercise patterns in a global social network of 1.1 million runners demonstrated that exercise is ‘contagious’, whose effect depends on gender and relative levels of activity [127].”
From Human-centred artificial intelligence for mobile health sensing: challenges and opportunities (2023) · cites this paper as [127]
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References 45 · Cited by 329
Research works printed but not linked: 4
- Gomez Rodriguez M., Leskovec J. & Krause A. in Proceedings of the 16th ACM SIGKDD, 1019–1028 (Washington, DC, USA, 2010).
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- Authors
- Aral, S., & Nicolaides, C.
- Affiliations
- Massachusetts Institute of Technology (US)
- Corresponding author
- Aral, Sinan
- Venue
- Nature Communications
- Published
- 2017-04-18
- Volume
- 8
- Issue
- 1
- Pages
- 14753-14753
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC5399289
- OpenAlex
- W2737079750
- Cited by
- 329
- References
- 45
- Citations by year
- 2026: 24 · 2025: 40 · 2024: 25 · 2023: 27 · 2022: 37 · 2021: 50 · 2020: 40 · 2019: 43 · 2018: 30 · 2017: 9 · 2016: 3 · 2015: 1
- FWCI
- 17.26
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Science Foundation (0953832)
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Opinion Dynamics and Social Influence
- Keywords
- social contagion, exercise behavior, running, network ties, embeddedness, structural diversity, complex contagion, behaviour change interventions
- MeSH terms
- Peer Influence, Female, Humans, Interpersonal Relations, Male, Models, Psychological, Running, Weather, Health Behavior, Social Networking
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