Detecting anomalies in Twitter stream for public security issues
Flora Amato, Giovanni Cozzolino, Antonino Mazzeo, Sara Romano · 2016
Social networking services gain more often interest for research goals in several fields and applications thanks to the big amount of data that users daily post on them. Knowledge that has accumulated in the social sites enables to catch the reflection of real world events. In this work we present a general framework for event detection from Twitter. The framework aims to collect tweets related to a particular social event, in order to filter and classify those which can be relevant to detect malicious actions in Twitter communities. Relevant tweets are processed to raise an alert in case of anomaly within the collected set.