Detecting latest local events from geotagged tweet streams

Abstract

Geotagged tweet streams contain invaluable information about the real-world local events like sports games, protests and traf-c accidents. Timely detecting and extracting such events has various applications but yet unsolved challenges. In this paper, we present DeLLe, a methodology for automatically Detecting Latest Local Events from geotagged tweet streams. DeLLe rst nds unusual locations which have aggregated unexpected number of tweets, and then ranks the unusual locations to select the top ones that are likely to be local event candidates. We evaluate DeLLe on the city of Seale, WA as well as a larger city of New York. e results show that the proposed method generally outperforms competitive baseline approaches.