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利用手机位置数据可视化新冠疫情引发的社会和行为变化

Visualizing Social and Behavior Change due to the Outbreak of COVID-19 Using Mobile Phone Location Data.

作者信息

Mizuno Takayuki, Ohnishi Takaaki, Watanabe Tsutomu

机构信息

National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, 101-8430 Japan.

The Canon Institute for Global Studies, 11th Floor, ShinMarunouchi Building, 5-1-1 Marunouchi, Chiyoda-ku, Tokyo, 100-6511 Japan.

出版信息

New Gener Comput. 2021;39(3-4):453-468. doi: 10.1007/s00354-021-00139-x. Epub 2021 Nov 2.

DOI:10.1007/s00354-021-00139-x
PMID:34744249
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8561084/
Abstract

We visualize the rates of stay-home for residents by region using the difference between day-time and night-time populations to detect residential areas, and then observing the numbers of people leaving residential areas. There are issues with measuring stay-home rates by observing numbers of people visiting downtown areas, such as central urban shopping centers and major train stations. The first is that we cannot eliminate the possibility that people will avoid areas being observed and go to other areas. The second is that for people visiting downtown areas, we cannot know where they reside. These issues can be resolved if we quantify the degree of stay-home using the number of people leaving residential areas. There are significant differences in stay-home levels by region throughout Japan. By this visualization, residents of each region can see whether their level of stay-home is adequate or not, and this can provide incentive toward compliance suited to the residents of the region.

摘要

我们通过利用白天和夜间人口的差异来检测居民区，从而可视化各地区居民的居家率，然后观察离开居民区的人数。通过观察前往市中心区域（如城市中央购物中心和主要火车站）的人数来衡量居家率存在一些问题。第一个问题是，我们无法排除人们避开被观察区域而前往其他区域的可能性。第二个问题是，对于前往市中心区域的人，我们无法知道他们居住在哪里。如果我们使用离开居民区的人数来量化居家程度，这些问题就可以得到解决。在日本各地，各地区的居家水平存在显著差异。通过这种可视化方式，每个地区的居民可以看到自己的居家水平是否足够，这可以为该地区居民遵守规定提供激励。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ea/8561084/d51e0f0f9d43/354_2021_139_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ea/8561084/5f4b2e1fbee2/354_2021_139_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ea/8561084/f361c3528549/354_2021_139_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ea/8561084/97acc02c1407/354_2021_139_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ea/8561084/d51e0f0f9d43/354_2021_139_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ea/8561084/5f4b2e1fbee2/354_2021_139_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ea/8561084/9442bdd26d9f/354_2021_139_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ea/8561084/b0773875127e/354_2021_139_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ea/8561084/0e4469132d6b/354_2021_139_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ea/8561084/fb7485bc29ba/354_2021_139_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ea/8561084/f361c3528549/354_2021_139_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ea/8561084/97acc02c1407/354_2021_139_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ea/8561084/d51e0f0f9d43/354_2021_139_Fig10_HTML.jpg

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