Distributed streaming reconstruction of information diffusion: poster

Abstract

Recent advances in social media have triggered a massive engagement of user population: a large part of people's lives has shifted to social media platforms and real events are reported while they are happening (e.g. in Twitter). As a result, such platforms have become an important source of information, being used by professionals as well, e.g. journalists, for fast access to news and events. Social media maintain an underlying network of social connections over which such information propagates. Information diffusion in social media has attracted attention, by analyzing how information is propagated from user to user and who is influenced by whom. Given the scale and speed of such information, systems that can keep up with such fast rates are required. In this poster, we present a system for real time reconstruction of information diffusion that encompass the challenges of analyzing fast data streams combined with large social graphs.