Characterizing diabetes, diet, exercise, and obesity comments on Twitter

•A multi-component semantic and linguistic framework was proposed to collect Twitter data, discover topics of interest about DDEO, and analyze the topics.•The characteristics of general public's opinions in regard to diabetes, diet, exercise, and obesity as expressed on 4.5 million tweets were analyzed.•The public perception of the relationship among diabetes, diet, exercise, and obesity was disclosed.•The possible practical applications of this research were discussed. Social media provide a platform for users to express their opinions and share information. Understanding public health opinions on social media, such as Twitter, offers a unique approach to characterizing common health issues such as diabetes, diet, exercise, and obesity (DDEO); however, collecting and analyzing a large scale conversational public health data set is a challenging research task. The goal of this research is to analyze the characteristics of the general public's opinions in regard to diabetes, diet, exercise and obesity (DDEO) as expressed on Twitter. A multi-component semantic and linguistic framework was developed to collect Twitter data, discover topics of interest about 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 and obesity (p