Detecting Train Delays using Railway Network Topology in Twitter
Author(s)
Wang, Yuanyuan
Nakaoka, Yusuke
Siriaraya, Panote
Kawai, Yukiko
Akiyama, Toyokazu
Issue Date
2018
Keyword(s)
topic propagation
railway topology
delay detection
real space and cyberspace
Twitter
Abstract
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.
Publisher
iSchools
Series/Report Name or Number
iConference 2018 Proceedings
Type of Resource
text
Language
eng
Permalink
http://hdl.handle.net/2142/100222
Copyright and License Information
Copyright 2018 is held by Yuanyuan Wang, Yusuke Nakaoka, Panote Siriaraya, Yukiko Kawai, Toyokazu Akiyama. Copyright permissions, when appropriate, must be obtained directly from the authors.
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