Abstract In recent years, subway has become an important transportation means for residents. Due to the huge passenger flow in metropolises, the urban metro network has become more and more complex. Some anomalies may have serious impact on the metro system and spread rapidly. Therefore, it is essential to find out the detail information of anomalies in the metro system. At the same time, mastering the causes of anomalies can help us understand conditions of the occurrences of anomalies. Currently, there are a large number of visualization studies about displaying the abnormal data of traffic, but most of them focus on road network. Even if there are some visualization studies about metro network, they mainly pay attention to the abnormal stations and the abnormal flows between stations instead of concentrating on exploring the abnormal reasons. In this paper, we propose a visual analytics system based on smart card and social network data. It provides multiple coordinated views to display valid information of abnormal stations intuitively and simultaneously, which can help us verify metro anomalies and abnormal section flow between stations. Besides, it also offers several views to have a quick glimpse of the causes of metro anomalies. A series of factual case studies and two system test experiments have verified the feasibility and effectiveness of our system. Graphic Abstract

中文翻译：

---

城市地铁网络异常客流可视化分析方法

摘要 近年来，地铁已成为居民的重要交通工具。由于大都市的巨大客流，城市地铁网络变得越来越复杂。一些异常可能会对地铁系统产生严重影响并迅速蔓延。因此，找出地铁系统异常的详细信息是必不可少的。同时，掌握异常发生的原因，有助于我们了解异常发生的条件。目前，有大量关于交通异常数据显示的可视化研究，但大多集中在道路网络上。即使有一些关于地铁网络的可视化研究，他们也主要关注异常站点和站点之间的异常流量，而不是专注于探索异常原因。在本文中，我们提出了一种基于智能卡和社交网络数据的可视化分析系统。提供多种协同视图，直观、同时显示异常站点的有效信息，帮助我们验证地铁异常和站间异常路段流量。此外，它还提供了多种视图，可以快速了解地铁异常的原因。一系列事实案例研究和两个系统测试实验验证了我们系统的可行性和有效性。图形摘要 它还提供了几种视图，可以快速了解地铁异常的原因。一系列事实案例研究和两个系统测试实验验证了我们系统的可行性和有效性。图形摘要 它还提供了几种视图，可以快速了解地铁异常的原因。一系列事实案例研究和两个系统测试实验验证了我们系统的可行性和有效性。图形摘要