TWEETS SHOW HOW DIFFERENT U.S. REGIONS LIKE TO EXERCISE

Researchers used machine learning to find and comb through exercise-related tweets from across the United States, unpacking regional and gender differences in exercise types and intensity levels. By analyzing the language of the tweets, this method was also able to show how different populations feel about different kinds of exercise.

“In most cases, lower-income communities tend to lack access to resources that encourage a healthy lifestyle,” says Elaine Nsoesie, an assistant professor of global health at the School of Public Health at Boston University and a data science faculty fellow at the Rafik B. Hariri Institute for Computing & Computational Science.

“By understanding differences in how people are exercising across different communities, we can design interventions that target the specific needs of those communities,” she says.

Full story at Futurity