Location-based burst detection algorithm for georeferenced document streams based on user's moving direction
Tomoki Matsui, Keiichi Tamura, Hajime Kitakami · 2013
Nowadays with the increasing attention being paid to social media, a huge number of georeferenced documents, which include location information, are posted on social media sites. People transmit and collect information over the Internet through these georeferenced documents, which are usually related to not only personal topics but also local topics and events. Detecting topics and events in georeferenced documents is effective in geo-location applications such as marketing, tourism informatics, and recommendation systems. Burstiness is one of the simplest and most effective criteria for extracting hot topics from a document stream. In this paper, we propose a novel method, which extends Klenberg's burst detection algorithm, for detecting location-based bursts in georeferenced documents by considering the user's moving direction. To evaluate the proposed burst detection algorithm, we used crawling tweets posted on the Twitter site. The experimental results show that our method can detect location-based bursts by considering user's moving direction.