Mobility Pattern Analysis during Russia-Ukraine War Using Twitter Location Data

被引:0
|
作者
Shu, Yupei [1 ]
Chen, Xu [2 ]
Di, Xuan [2 ]
机构
[1] Columbia Univ, Dept Ind Engn & Operat Res, New York, NY 10027 USA
[2] Columbia Univ, Dept Civil Engn & Engn Mech, New York, NY 10027 USA
关键词
gyration; social media; Russia-Ukraine war; MODELS;
D O I
10.3390/info15020076
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper aims to use location-based social media data to infer the impact of the Russia-Ukraine war on human mobility. We examine the impact of the Russia-Ukraine war on changes in human mobility in terms of the spatial range of check-in locations using social media location data. Specifically, we collect users' check-in location data from Twitter and analyze the average gyration of check-ins from a region across the timeline of major events associated with the war. Change-point detection is performed on these time-series check-ins to identify the timeline of abrupt changes, which are shown to be consistent with the timing of a series of sanctions and policies. We find that war-related events may contribute secondary impacts (e.g., the surge in gas prices) to users' travel patterns. The impact of the Russia-Ukraine war on users' travel patterns can differ based on their own scope. Our case study demonstrates that users' gyration in Warsaw, Paris, and Berlin experienced a decrease of over 50% during periods of gas price surges. These changes in users' gyration patterns were particularly noticeable in neighboring countries like Poland compared to the other three countries. The findings of this study can assist policymakers, regulators, and urban planners to evaluate the impact of the war and to be adaptable to city planning after the war.
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页数:12
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