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Communicating diabetes and diets on Twitter - a semantic content analysis

Published Online:pp 8-24https://doi.org/10.1504/IJNVO.2016.075133

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

Keywords

diabetes, diets, health communication, health information systems, HIS, health information dissemination, information sharing, social media, social networks, tweets, Twitter, semantic content analysis, public opinion mapping, public sentiment