Detecting anomalies in Twitter stream for public security issues

摘要: 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 has accumulated social sites enables catch reflection real world events. In this work we present a general framework event detection from Twitter. The aims collect tweets related particular event, order filter classify those which can be relevant detect malicious actions Twitter communities. Relevant are processed raise an alert case anomaly within collected set.