Analysing and monitoring Social Networking activities raise multiple challenges for the evolution of Service Oriented Systems Engineering. This is particularly evident for event detection in social networks and, more in general, for large-scale Social Analytics, which require continuous processing of data. In this paper we present a service oriented framework exploring effective ways to leverage the opportunities coming from innovations and evolutions in computational power, storage, and infrastructures, with particular focus on modern architectures including in-memory database technology, in-database computation, massive parallel processing, Open Data Services, and scalability with multi-node clusters in Cloud. A prototype of this system was experimented in the contest of a specific kind of social event, an art exhibition of sculptures, where the system collected and analyzed in real-time the tweets issued in an entire region, including exhibition sites, and continuously updated analytical dashboards placed in one of the exhibition rooms.
['Angelo Chianese', 'Francesco Piccialli']
A Service Oriented Framework for Analysing Social Network Activities