Formation of Social Ties Influences Food Choice: A Campus-Wide Longitudinal Study
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Abstract (arXiv)
Nutrition is a key determinant of long-term health, and social influence has long been theorized to be a key determinant of nutrition. It has been difficult to quantify the postulated role of social influence on nutrition using traditional methods such as surveys, due to the typically small scale and short duration of studies. To overcome these limitations, we leverage a novel source of data: logs of 38 million food purchases made over an 8-year period on the Ecole Polytechnique Federale de Lausanne (EPFL) university campus, linked to anonymized individuals via the smartcards used to make on-campus purchases. In a longitudinal observational study, we ask: How is a person's food choice affected by eating with someone else whose own food choice is healthy vs. unhealthy? To estimate causal effects from the passively observed log data, we control confounds in a matched quasi-experimental design: we identify focal users who at first do not have any regular eating partners but then start eating with a fixed partner regularly, and we match focal users into comparison pairs such that paired users are nearly identical with respect to covariates measured before acquiring the partner, where the two focal users' new eating partners diverge in the healthiness of their respective food choice. A difference-in-differences analysis of the paired data yields clear evidence of social influence: focal users acquiring a healthy-eating partner change their habits significantly more toward healthy foods than focal users acquiring an unhealthy-eating partner. We further identify foods whose purchase frequency is impacted significantly by the eating partner's healthiness of food choice. Beyond the main results, the work demonstrates the utility of passively sensed food purchase logs for deriving insights, with the potential of informing the design of public health interventions and food offerings.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 94 references that are in the map. First posted on arXiv 17 Feb 2021.
Builds on
8 of 94 references.
References · 8
- 2016Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locationscited by 8
- 2017Is Saki #delicious? The Food Perception Gap on Instagram and Its Relation to Healthcited by 8
- 2018Machine-learned epidemiology: real-time detection of foodborne illness at scalecited by 6
- 2013From Cookies to Cooks: Insights on Dietary Patterns via Analysis of Web Usage Logscited by 4
- 2016Extracting Food Substitutes From Food Diary via Distributional Similaritycited by 4
- 2016Fetishizing Food in Digital Age: #foodporn Around the Worldcited by 3
- 2019Large-scale and high-resolution analysis of food purchases and health outcomescited by 3
- 2014You Tweet What You Eat: Studying Food Consumption Through Twittercited by 2
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Citing papers per year: 2026: 1.
1 paper.