Food Tweets Can Reveal How Healthy Communities Are
18 Oct 2016 --- Scientists at the University of Utah have suggested that tracking tweets about food can reveal a lot about a community’s health, adding that communities expressing positive sentiments about healthy foods online, are more likely to be healthier overall.
The study surveyed nearly 80 million Twitter messages, a random sample of one percent of publicly available, geotagged tweets - over the course of one year.
They then sorted through the 4 million tweets about food for ones that fell on opposite ends of the health spectrum: tweets mentioning fast food restaurants, or lean meats, fruits, veggies or nuts.
Besides hinting at which foods are popular with the general population, the researchers say that the tweets may reveal something about our health.
The study found that "Coffee" was the most tweeted food in the continental U.S. between mid-2014 to mid-2015 followed by "beer" then "pizza".
Out of that top 10 list, only the fourth most popular food-related item, "Starbucks", fit into the fast food category. The seventh, "chicken", was the only one considered as healthy food.
However, the real insights came after cross-referencing the two types of food tweets with information about the neighborhoods they came from, including census data and health surveys.
They found, for instance, that tweets from poor neighborhoods, and regions with large households, were less likely to mention healthy foods. Also, people in areas dense with fast food restaurants tweeted more often about fast food.
The study also found that positive sentiments towards healthy foods were broadly related to fewer deaths and lower rates of chronic health conditions.
Twitter has already been used to track health by gauging the prevalence of smoking and finding the source of outbreaks. The difference here is that these types of comparisons could provide clues as to how our surrounding neighborhood - the environment that we live, work, and play in, impacts our health and well-being.
"Our data could be telling us that certain neighborhoods have fewer resources to support healthy diets," says Quynh Nguyen, Ph.D., an assistant professor at the University of Utah College of Health.
She explains that neighborhoods laden with fast food restaurants could perhaps benefit from having more supermarkets or farm stands that sell fresh produce.
However, she also adds that it’s too early to draw firm conclusions about what all this new data could mean, adding that tweets are biased, and that Twitter users represent only a fraction of the population and skew toward 18 to 49 year olds.
Furthermore, people are more likely to broadcast certain foods over others, giving a warped perception of what foods are genuinely popular – for example, you might be more inclined to tell your friends about a celebratory cupcake than a stack of celery sticks.
Additionally, automated algorithms categorized tweets with about 85 percent accuracy. For example, initially computers labeled messages about NBA basketball player Stephen Curry as food tweets. After noting the error, the researchers excluded those tweets and only counted messages with an additional description such as "chicken curry" or "Masala curry".
Future versions of the programs will more fully integrate machine learning, which should improve results, but the authors say the approach is too powerful to ignore.
"This is a promising new, cost-effective method for studying the social and environmental influences on health," says senior author Ming Wen, Ph.D., professor of sociology at the University of Utah.
