You Are What You Tweet: Connecting the Geographic Variation in America's Obesity Rate to Twitter Content.

David Meyre,Saikou Diallo,Ross Joseph Gore,Jose Padilla

doi:10.1371/journal.pone.0133505

Abstract

We conduct a detailed investigation of the relationship among the obesity rate of urban areas and expressions of happiness, diet and physical activity on social media. We do so by analyzing a massive, geo-tagged data set comprising over 200 million words generated over the course of 2012 and 2013 on the social network service Twitter. Among many results, we show that areas with lower obesity rates: (1) have happier tweets and frequently discuss (2) food, particularly fruits and vegetables, and (3) physical activities of any intensity. Additionally, we provide evidence that each of these results offer different and unique insight into the variation of the obesity rate in urban areas within the United States. Our work shows how the contents of social media may potentially be used to estimate real-time, population-scale measures of factors related to obesity.

Highlights

Obesity is becoming increasingly problematic and common in the United States population [1, 2]
Mitchell et al showed that the happiness of tweets are correlated with the 2011 obesity rate in Metropolitan Statistical Area (MSA) [12]
To validate this result we explore the correlation between the happiness of a tweet and the obesity rate of MSAs in our random sample of Twitter data

Summary

Introduction

Obesity is becoming increasingly problematic and common in the United States population [1, 2]. More than one-third of U.S adults are obese resulting in an annual medical cost of over $150 billion dollars [1, 3, 4]. These medical costs occur because obese people are significantly more prone to the leading causes of preventable death including: heart disease, stroke and type 2 diabetes [5]. Obese individuals have a BMI of 30 kg m2 or greater. Obesity rate is defined as the percentage of the people in a Metropolitan Statistical Area (MSA) who have a BMI of 30 kg m2 or greater [2, 6]

Methods

Results

Conclusion