过程(计算)
比例(比率)
数据收集
计算机科学
数据科学
人力资源
人体动力学
运输工程
工程类
地理
地图学
人工智能
操作系统
统计
经济
管理
数学
作者
Qi Wang,John E. Taylor
出处
期刊:Journal of Computing in Civil Engineering
[American Society of Civil Engineers]
日期:2016-03-01
卷期号:30 (2)
被引量:50
标识
DOI:10.1061/(asce)cp.1943-5487.0000469
摘要
Human mobility is central to our understanding of design, planning, and development of civil infrastructure in urban areas. Although researchers have spent considerable effort in studying human mobility patterns, there is still a lack of human movement data with satisfactory quantity and accuracy. This paper introduces an approach to collecting human mobility data and discusses analyses conducted. A comprehensive process map was developed to collect human movement data from Twitter. The map included four steps and multiple programmed modules, processes, and databases. Via the process map, human mobility data was collected, and a one-month subset from New York City was retrieved to use in a case study. Results from the case study aligned with findings from existing human mobility research, and thus Twitter was confirmed to be a viable resource for studying city-scale human mobility. Large-scale human mobility data will allow researchers to study the interdependence of human activity and civil infrastructure as a way to deepen understanding of important city-scale phenomena such as evacuation during extreme events and the spread of epidemics.
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