A Cloud Enabled Social Media Monitoring Platform for Events Detection and Prediction

The data mined from social networks has been shown to have an inherent wealth of information. However the heterogeneous nature of this data along with difficulties in predetermining its rate and source makes collecting and aggregating it an often inefficiently run task. This paper presents a platform which leverages some of the architecture and features of Cloud computing in order to dynamically scale resources according to data rate, so as to collect and parse data from a variety of social media sources in an economical manner. The nature of the platform means that it may be applied to a variety of social network monitoring tasks, which may take advantage of the dynamic and economical nature of Cloud-based architectures. This paper addresses a gap in the current literature and proposes a novel Cloud Enabled Social Media Monitoring Platform for Events Detection and Prediction.