Detection and Reinforcement of Celiac Communities on Twitter Argentina

Abstract

Social Networks have shown great growth relating the number of their users and generated content. For example, Twitter is used as a means to gather support, express ideas and opinions on various topics or interact with users with similar interests. In the latter case, the idea of community formation appears, that is, groups of users that are more closely related to each other than the rest of the nodes in the network. In this work we propose the detection of the community of users of Argentina interested in the celiac disease. We apply a series of techniques to detect and characterize them. In addition, we propose and use a methodology for the detection of more influential and active nodes (users), showing how the community can be reinforced by the recommendation of some particular links. The results show that with only a low percentage of accepted recommendation the network becomes denser and average distance between two users decreases quickly, thus improving the spread of information.