contributor author | Qi Wang | |
contributor author | John E. Taylor | |
date accessioned | 2017-12-30T13:05:02Z | |
date available | 2017-12-30T13:05:02Z | |
date issued | 2016 | |
identifier other | %28ASCE%29CP.1943-5487.0000469.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4245448 | |
description abstract | 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. | |
publisher | American Society of Civil Engineers | |
title | Process Map for Urban-Human Mobility and Civil Infrastructure Data Collection Using Geosocial Networking Platforms | |
type | Journal Paper | |
journal volume | 30 | |
journal issue | 2 | |
journal title | Journal of Computing in Civil Engineering | |
identifier doi | 10.1061/(ASCE)CP.1943-5487.0000469 | |
page | 04015004 | |
tree | Journal of Computing in Civil Engineering:;2016:;Volume ( 030 ):;issue: 002 | |
contenttype | Fulltext | |