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Social media provide a platform for users to express their opinions and shareinformation. Understanding public health opinions on social media, such asTwitter, offers a unique approach to characterizing common health issues suchas diabetes, diet, exercise, and obesity (DDEO), however, collecting andanalyzing a large scale conversational public health data set is a challengingresearch task. The goal of this research is to analyze the characteristics ofthe general public's opinions in regard to diabetes, diet, exercise and obesity(DDEO) as expressed on Twitter. A multi-component semantic and linguisticframework was developed to collect Twitter data, discover topics of interestabout DDEO, and analyze the topics. From the extracted 4.5 million tweets, 8%of tweets discussed diabetes, 23.7% diet, 16.6% exercise, and 51.7% obesity.The strongest correlation among the topics was determined between exercise andobesity. Other notable correlations were: diabetes and obesity, and diet andobesity DDEO terms were also identified as subtopics of each of the DDEOtopics. The frequent subtopics discussed along with Diabetes, excluding theDDEO terms themselves, were blood pressure, heart attack, yoga, and Alzheimer.The non-DDEO subtopics for Diet included vegetarian, pregnancy, celebrities,weight loss, religious, and mental health, while subtopics for Exerciseincluded computer games, brain, fitness, and daily plan. Non-DDEO subtopics forObesity included Alzheimer, cancer, and children. With 2.67 billion socialmedia users in 2016, publicly available data such as Twitter posts can beutilized to support clinical providers, public health experts, and socialscientists in better understanding common public opinions in regard todiabetes, diet, exercise, and obesity.

Characterizing Diabetes, Diet, Exercise, and Obesity Comments on Twitter