Study reveals what tweets say about our lifestyle


Tapping into the Twitter stream could help researchers understand how healthy people's lifestyles are and how to target improved public health, according to a recent study.

Using geotagged tweets, researchers at the Universities of Utah and Washington were able to build a map of the U.S. by neighborhood, with indicators of how happy and active people in that neighborhood are and what their diets are like.

"Overall I think the patterns make sense, more fast food restaurants in the area are correlated with more fast food mentions, but I was surprised that coffee was so highly ranked," said lead author Quynh C. Nguyen of the University of Utah College of Health in Salt Lake City.

The researchers collected 1 percent of randomly selected tweets that were tagged with a geographic location between April 2015 and March 2016. That yielded 80 million tweets from 603,000 users in the contiguous U.S.

They then built several versions of a machine learning algorithm to sort the tweets by indicators of happiness, activity and diet. The results were checked by humans to make sure tweets weren't misunderstood by the machine - for instance, in one case, the algorithm identified tweets about basketball player Stephen Curry as food tweets, before researchers corrected it.

The study team next mapped their sorted tweets to 2010 census tracts and ZIP code areas.

About 20 percent of tweets were classified as happy. People tend to only use a few words to talk about food or activity, so the researchers only used 25 search terms.

Proximity to fitness centers or parks only modestly predicted mentions of physical activity, but density of fast food restaurants by neighborhood did predict how many mentions of fast food people in the neighborhood made.

At the state level, more positive mentions of physical activity and healthy foods, as well as happiness, were associated with lower all-cause mortality and the prevalence of chronic conditions like obesity and diabetes, according to the report online October 17th in the Journal of Medical Internet Research Public Health and Surveillance.

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