Mitigating biases in big mobility data: a case study of monitoring large-scale transit systems-Reference-Cited by-同舟云学术

Mitigating biases in big mobility data: a case study of monitoring large-scale transit systems

Published:2024-07-17 Issue: Volume: Page:1-14
ISSN:1942-7867
Container-title:Transportation Letters
language:en
Short-container-title:Transportation Letters

Author:

Wang Feilong¹^ORCID,Ban Xuegang (Jeff)²,Chen Peng³,Liu Chenxi²,Zhao Rong⁴

Affiliation:

1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China

2. Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA

3. School of Public Affairs, University of South Florida, Tampa, FL, USA

4. Department of Industrial Engineering, Dongguan University of Technology, Dongguan, China

Funder

Basic and Applied Basic Research Foundation of Guangdong Province

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/19427867.2024.2379703

Reference44 articles.

1. Aktay A. S. Bavadekar G. Cossoul J. Davis D. Desfontaines A. Fabrikant E. Gabrilovich et al. “Google COVID-19 Community Mobility Reports: Anonymization Process Description (Version 1.1).” Accessed July 26 2022. http://arxiv.org/abs/2004.04145.

2. Apple. “Apple Makes Mobility Data Available to Aid COVID-19 Efforts.” Apple Newsroom. Accessed July 26 2022. https://www.apple.com/newsroom/2020/04/apple-makes-mobility-data-available-to-aid-covid-19-efforts/.

3. Comparative Perspective of Human Behavior Patterns to Uncover Ownership Bias among Mobile Phone Users

4. Managing bias and unfairness in data for decision support: a survey of machine learning and data engineering approaches to identify and mitigate bias and unfairness within data management and analytics systems