An integrated system for social information discovery

Everyday millions of contents are generated and shared over the most popular social network. Enterprises have already realized the usefulness of social networks to enable marketing campaigns and communicate with their customers. However, only few enterprises use social network as an active source of information, interacting with the network's users in (near-)real time, e.g. for crowdsourcing and leveraging open-innovation. To encourage and facilitate this use of networks, we believe it is needed an information discovery system which elaborates simultaneously over more-than-one networks in an integrated scenario. Such a system has to be able to handle the speed at which the contents of social network are generated, the huge amount of available data and dynamism at which networks evolve and new kind of content are shared. Furthermore, the system has to ensure a quick response time. In this work we propose a methodology to design this kind of system and present the experience gained in the development of an information discovery system based on Exploratory Data Analysis and aimed at analyzing text contents from two social networks: Facebook and Twitter.