S-InTime: A social cloud analytical service oriented system

Abstract

Social Networking activities raise multiple challenges for the evolution of Service Oriented Systems Engineering. The purpose of this research work is to demonstrate how a specific core technology and cloud platform with micro-services can be designed and used for performing data-intensive computations and implementing services in a real case of social analytics. In detail, we face the challenges of real-time data-intensive processing with the systematic application of in-memory view-based information modeling & computation, which is based on different types of non-materialized views without pre-aggregation of data. Finally, our study presents and compares design alternatives for these mappings, and demonstrates their effective application for implementing a large set of social analytics service types, with particular reference to the case of streaming sources of twitter data. A prototype of this system was experimented in the contest of a specific kind of social event, a permanent exhibition of Artworks, 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.