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​Can joining a social network prompt us to do more exercise?

​Stanford computer scientists find that people who used a smartphone app to track exercise activity walked a little more each day once they joined the app’s optional social network.


	
		
			
				Joining a social network boosted the physical activity of people who had already shown a commitment to exercise. | Illustration by Stefani Billings
			
		
	

 





Joining a social network boosted the physical activity of people who had already shown a commitment to exercise. | Illustration by Stefani Billings




 

Online social networks are all around us, yet there is little understanding of how they influence our offline activities.

How do online networks influence our real-world behavior?

Stanford computer scientists have shed light on this question in a paper that analyzes exercise data collected by the Argus mobile health platform. This smartphone app tracks various activities from heart rate to daily exercise. The app also allows individuals to share their data with friends through a social networking feature.

The researchers – associate professor of computer science Jure Leskovec, PhD candidate Tim Althoff and former Stanford research assistant Pranav Jindal – analyzed 791 million activities by 6 million app users over five years. All of the data was anonymous, but it was linked to demographic factors such as age, gender and body mass index. Some of the 6 million people in the sample used the app only to record their exercise and health activity. Other individuals opted to join the app’s social network. This allowed the researchers to see whether and how these joiners changed their real-world exercise behavior after opting into the social network.

By analyzing and comparing this data, the researchers have shown that joining the social network influenced the app’s users to increase their physical activity by 7 percent, or by approximately 400 steps daily.

“We were able to show that network connections influence us to be more active and that social network users are not simply more intrinsically motivated to exercise,” Althoff said.

This social networking effect held up for a surprisingly long period of 20 weeks. Users that engaged with others on the social network were exposed to their friends’ activities and received notifications when others exercised or sent them encouraging notes. The Stanford study showed that this influenced people to be more active themselves – and potentially improve their health.

The fact that the anonymous data had demographic tags allowed the researchers to make some interesting findings about which sorts of users were more likely to benefit by joining the optional social network. For instance, women were most influenced by female exercise buddies. They increased their daily activity by 52 percent more when they buddied up with another woman, as compared to when they received a friend request from a man. Age also mattered. Participants in the 30–45-year-old age bracket saw the biggest changes in activity, more than the 18–30-year-olds who, the researchers suggest, may take social networking more for granted.

Another interesting finding was that people who described themselves as obese had a bigger exercise boost from social networking than people who self-described as normal weight or merely overweight. This was particularly surprising because obese people typically walk far less than normal weight people, suggesting that engagement in social networks could be particularly helpful for obese people trying to improve their health.

The researchers were also able to show which sorts of social connections were most likely to have the greatest influence on an individual’s behavior. These findings could help to design more effective support communities and social networks that lead to healthier lifestyles. “Online social networks are a powerful tool to provide social support and influence healthy behaviors,” said Leskovec.

The researchers acknowledge Azumio, the company that produces the Argus app, for providing the anonymized dataset for this study. This work was supported by public and private funding sources, including the Stanford Data Sciences Initiative and the Mobilize Center.

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