This paper presents a novel train delay detection method based on topic propagation analysis of geo-tagged tweets between railway stations. Our goal is to detect traffic accidents and to predict train delays in railway network topology by tracing how relevant tweets propagate in real space and cyberspace. In our method, we utilize railway network as the topology of real space, and extract the topology of social network that is mapped on the railway network. This permits observing the influence of delays on stations with a few tweets, or predicting related tweets of affected stations even if the tweets contain indirect topics about delays
