Analysis and Visualization of Personal Data: the Value of Images in the Social Networks

The goal of this research project is the analysis and development of tools to highlight and interpret personal data that is freely shared on the social networks of the web. Starting from the premise that images taken by mobile phones can be considered to all effects personal data representing values that can be displayed through a system of interactive maps, we will develop a strategy to identify the means for comparing different sets of data in order to reveal temporal and geographical information. The current project is an online platform for collecting and displaying interpolated data obtained by cross-reading the social networks Twitter and Instagram. The comparison between tweets and the pictures shared on Instagram will find some correlations that will be read and interpreted through an interactive interface. The results will be visualised on the basis of their hashtags and geolocation. Given a defined time interval, a geographical reference located in metropolitan areas, and a matrix of different hashtags, the software will create interactive maps by collecting different sets of data. This will provide the user with a tool for analysing and interpreting certain complex phenomena related to certain specific socio-cultural aspects. The selection of case studies for the research has been carried out mainly within the social context that revolves around fitness. The underlying reason is that the use of camera images is strongly linked to personal motivation and self-confirmation. The correlation between the satisfaction of achieving a specific performance in sports (though not a professional one) and the temporal and geo-referenced context becomes a tool to analyse and understand complex dynamics evolving within a multifaceted environment such as the one that orbits around sharing online pictures of the results as self-confirmation.