Detecting Local Events by Analyzing Spatiotemporal Locality of Tweets

Abstract

In this paper, we study how to detect local events regardless of the size and the type using Twitter, a social networking service. Our method is based on the observation that relevant tweets are simultaneously posted from the place where a local event is happening. Specifically, our method first extracts the place where and the time when multiple tweets are posted by using clustering techniques and then detects the co-occurrence of key terms in each cluster to find local events. For determining key terms, our method also leverages spatiotemporal locality of tweets. From experimental results on tweet data from 9:00 to 15:00 on October 9, 2011, we confirmed the effectiveness of our method.