An innovative framework for effectively and efficiently supporting big data analytics over geo-located mobile social media

Mobile Social Media are gaining momentum in the broader context of Big Data Analytics, where the main issue is represented by the problem of extracting interesting and actionable knowledge from big data repositories. Mobile social media sources like Twitter and Instagram are indeed producing massive amounts of data (namely, posts) that represent a very rich source of knowledge for predictive analytics. In line with this emerging trend, this paper proposes an innovative approach for effectively and efficiently supporting big data analytics over geo-localized mobile social media, with particular emphasis with the context of modern tourist information systems. In this context, the innovative FollowMe suite, which implements the proposed methodology, is also described in details. We complement our analytical contribution with a real-life case study focusing on the EXPO 2015 event in Milan, Italy which clearly shows benefits and potentialities of our proposed big data analytics framework.