Social Media Gives Insight on Training Patterns
Researchers use AI to mine twitter data for physical activity trends.
Boston University School of Public Health researchers used machine learning (artificial intelligence) to analyze exercise-related tweets. The goal was to understand how gender and regional differences influenced some exercise behaviors across the U.S.
Walking was the most popular activity. Western women and Midwestern men did more intensive exercise than those in any other region. The South had the biggest gender gap in exercise intensity.
The study is available in BMJ Open Sport & Exercise Medicine (2019; 5 [e0005667]).
Shirley Eichenberger-Archer, JD, MA
Shirley Eichenberger-Archer, JD, MA, is an internationally acknowledged integrative health and mindfulness specialist, best-selling author of 16 fitness and wellness books translated into multiple languages and sold worldwide, award-winning health journalist, contributing editor to Fitness Journal, media spokesperson, and IDEA's 2008 Fitness Instructor of the Year. She's a 25-year industry veteran and former health and fitness educator at the Stanford Prevention Research Center, who has served on multiple industry committees and co-authored trade books and manuals for ACE, ACSM and YMCA of the USA. She has appeared on TV worldwide and was a featured trainer on America's Next Top Model.
