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 asa means to gather support, express ideas and opinions on various topicsor interact with users with similar interests. In the latter case, the ideaof community formation appears, that is, groups of users that are moreclosely 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 ofArgentina interested in the celiac disease. We apply a series of techniques to detect and characterize them. In addition, we propose anduse 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 lowpercentage of accepted recommendation the network becomes denser andaverage distance between two users decreases quickly, thus improving thespread of information.