![]() ![]() ![]() Data is available on request to the NetHealth project committee via emails to The research reported in this paper was supported by the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health under award number R01HL117757. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: Data cannot be made publicly available for the reason that public availability would compromise participant privacy. Received: MaAccepted: Published: June 6, 2019Ĭopyright: © 2019 Lin et al. Using a large longitudinal data set of students enrolled in the NetHealth study at the University of Notre Dame, we show that the NetCARE method improves the overall prediction performance over the baseline models-that use demographics and physical attributes-by 38%, 65%, 55%, and 54% for the wellness states-stress, happiness, positive attitude, and self-assessed health-considered in this paper.Ĭitation: Lin S, Faust L, Robles-Granda P, Kajdanowicz T, Chawla NV (2019) Social network structure is predictive of health and wellness. We develop a method called the Network-Driven health predictor (NetCARE) that leverages features representative of social network structure. In this paper, we investigate whether the structure or topology of a social network offers additional insight and predictability on an individual’s health and wellness. While researchers have studied social networks as a driver for diffusion of influences and behavior, it is less understood how the structure or topology of the network, in itself, impacts an individual’s health behavior and wellness state. ![]() Social networks influence health-related behavior, such as obesity and smoking. ![]()
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