Separating the Wheat from the Chaff: Events Detection in Twitter Data

Abstract

In this paper we present a system for the detection and validation of macro and micro-events in cities (e.g. concerts, business meetings, car accidents) through the analysis of geolocalized messages from Twitter. A simple but effective method is proposed for unknown event detection designed to alleviate computational issues in traditional approaches. The method is exploited by a web interface that in addition to visualizing the results of the automatic computation exposes interactive tools to inspect, validate the data and refine the processing pipeline. Researchers can exploit the web application for the rapid creation of macro and micro-events datasets of geolocalized messages currently unavailable and needed to improve supervised and unsupervised events classification on Twitter. The system has been evaluated in terms of precision.