The Spread of Physical Activity Through Social Networks
Abstract
We study the evolution of daily physical activity of 44.5K
users on the Fitbit social network over a period of eight
months. A time-aggregated analysis shows that average alter activity, gender, and body mass index (BMI) are significantly predictive of ego activity when controlling for ego
BMI, gender, and number of friends. The direction and
effect size of the associations surfaced vary when considering chronic conditions self-reported by a large portion of the
users including diabetes, dyslipidemia, hypertension and depression. When considering the co-evolution of activity and
friendship on a month by month basis in a within-subject
analysis, we show via fixed effects modeling that the fluctuations in average alter activity significantly predict fluctuations in ego activity. Finally, we investigate the causal
factors that may drive change of physical activity over time.
We leverage a class of novel non-parametric statistical tests
to rule out homophily as the sole source of dependence in activity, even in the presence of unobserved individual traits.