Communicating diabetes and diets on Twitter – a semantic content analysis

Abstract

<div> This paper analyses: 1) the semantic content of tweets discussing</div> <div> diabetes and diets: 2) the conversational connections of those tweeting and</div> <div> those being mentioned in the tweets. The content analysis of the tweets aims at</div> <div> mapping what kinds of diets are mentioned in conversations about diabetes and</div> <div> in what context. Our data consists of 9,042 tweets containing the words</div> <div> &lsquo;diabetes&rsquo; and &lsquo;diet&rsquo;. The findings indicate that analysing Twitter conversations</div> <div> can be a fruitful and an efficient way to map public opinions about diabetes and</div> <div> diets, as well as other medical issues that concern many people. The results also</div> <div> showed that many private persons act as diabetes advocates spreading</div> <div> information and news about diabetes and diets. Surveying these topics can be</div> <div> useful for healthcare practitioners; as these are in contact with patients with</div> <div> diabetes, it is important that they are aware of both the most discussed topics</div> <div> and the most common information sources, who are often laymen.</div>