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.
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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.
“Right now we’re correlating it with county-level and state-level
health outcomes,” which will hopefully be helpful for health
researchers in the future, Nguyen told Reuters Health.
“We don’t think the data can be taken as 100 percent a food diary;
what we can see is what people are willing to share,” she said.
People are very willing to share about coffee, in particular, which
may be due to its “social capital,” she noted.
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“There’s a certain image-crafting associated with being online,”
Nguyen said.
Twitter users also are not a perfect sample of people in the U.S.,
she said.
“It’s important for researchers to utilize meaningful data to
understand the underlying conditions that shape the health of
communities and individuals and to identify inequities in health
that we can do something about,” Jennifer L. Black of the Faculty of
Land and Food Systems at The University of British Columbia in
Vancouver said by email.
“Because twitter and social media are so new as sources of data and
sources of health information, I don’t think we yet know what the
full potential is for tweets to shape health behaviors,” said Black,
who was not part of the new study.
Twitter may not tell us what people are eating and doing, but it
provides a sense of what people are saying and writing, Black told
Reuters Health.
“Twitter and social media may be able to tell us something about
peoples’ experiences living in neighborhoods with barriers to
accessing healthy/fresh food,” Black added. “In the coming years it
will be important for researchers as well as students and emerging
food and nutrition professionals to gain insight about how people
use social media.”
SOURCE: http://bit.ly/2doQT6O
JMIR Public Health Surveill 2016.
[© 2016 Thomson Reuters. All rights
reserved.] Copyright 2016 Reuters. All rights reserved. This material may not be published,
broadcast, rewritten or redistributed.
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