Detecting Location-Based Enumerating Bursts in Georeferenced Micro-Posts

Nowadays, a large number of georeferenced micro-posts, i.e., short messages including location information, are posted on social media sites. People transmit and collect information over the Internet through these georeferenced micro-posts, which are usually related to not only personal topics but also local topics and events. Detecting local topics and events in georeferenced micro-posts is beneficial for many different geo-mobile application domains. Burstiness is one of the simplest and most effective criteria for extracting hot topics and events in micro-posts. In this paper, we propose a novel burst detection algorithm for detecting location-based enumerating bursts in georeferenced micro-posts. To evaluate the proposed burst detection algorithm, we used an actual set of georeferenced micro-posts, which are crawling tweets posted on the Twitter site. The experimental results show that our new burst detection algorithm can detect location-based enumerating bursts.