Detection methods for disaster by lexical patterns

Abstract

Recently, there is lots of interesting about Bigdata in Korea. Social Bigdata which is created by socialmedia has people’s opinion and idea, so government and other organizations want to use social Bigdata to find out public opinion and information. Utilization of this social Bigdata has been studied in disaster management. In our institute, we studied a way to quickly detecting disaster occurrence through the analysis of social Bigdata. In this paper, we describe the detecting method using the lexical patterns, and we present the results of applying this method on tweets related to three types of disaster. There are other results depending on the types of disaster. In this experience, tweets of collapse accident are the best result to apply the lexical patterns(94% accuracy). So the possibility of detection disaster using the lexical patterns was confirmed.