Mapping obesity & diabetes' representation on Twitter: the Italian case

One of the main functions of public health is to monitor the health of the population to identify health problems and priorities. Social media is increasingly used to promote it. The study aims at investigating the field of diabetes and obesity and the related Tweets in the health and disease framework. The database extracted using academic API (Application Programming Interface) enabled the study to be managed with content analysis and sentiment analysis techniques (Gabarron et al., 2019). These two analysis techniques are some of the tools of choice for the goals that have been set. The content analysis facilitates the representation of a concept and a connection between two or more concepts, such as diabetes and obesity, on a purely textual social platform such as Twitter (Amaturo and Punziano, 2013). The sentiment analysis enables the exploration of the emotional side connected to the data collected relating to the representation of those concepts (Gilbert, 2016). The results show a variety of representations connected to the two concepts and their correlations. From them, it was possible to produce some clusters of elementary contexts and to structure narrative and representative dimensions of the concepts investigated with regard to the social platform (Lancia, 2012). The use of sentiment analysis and content analysis and the output of cluster to represent complex contexts such as diabetes and obesity for a social media community could increase knowledge of how virtual platforms impact fragile categories, facilitating concrete relapses in public health strategies.