Event Duration Detection on Microblogging

TLDR: This paper proposes an issue of event duration detection and chooses rain as the target event, and proposes a wavelet-based and aging-based method to detect the beginning of the rain event and its duration.

Abstract: Microblog users often post what they observe in the surroundings, making it possible to use such microblog data to perform event detection. In this paper, we propose an issue of event duration detection and choose rain as our target event. Our goal is to construct an online virtual weather station, which reports local weather condition such as rain with the microblog data. Different from previous work focusing on earthquake, rain is a relatively minor event and may continue for a period of time. The virtual station, therefore, needs to detect not only when it starts but also when it finishes. The system trains a classifier to extract the event of interest. A wavelet-based method and aging-based method are proposed to detect the beginning of the rain event and its duration, respectively. Our experiments are conducted on real data, collected from Twitter and online weather stations. The results of experiments show the feasibility of virtual weather system. Our user behavior analysis also explains why the system works.