Article,
Scalable Social Analytics for Online Communities
IEEE Special Technical Community on Social Networks e-letter, (2013)
Abstract
With the constantly growing ecosphere of online communities, their managers, operators and members can hugely benefit from a rich set of tools to successfully understand, control, exploit and utilise them. This requires to extract reusable, interpretable analytics in real time from the streams of dynamically, socially produced data. In this article, we summarise our efforts in the context of the ROBUST project on producing a suite of novel, highly scalable methods and tools to enable this, aligned along four non-disjoint dimensions: structural analysis, behavioural analysis, content/social-semantic analysis and cross-community analysis.
