Papers – Platial Analysis Lab

New research highlights gender differences in urban running

March 3, 2025

Our recent publication identifies gender differences in urban running patterns with the objective of shaping safer, more inclusive cities…

New publication examining disparities in NYC transportation recovery

April 8, 2024

In a recent paper published in Computers, Environment and Urban Systems, Dan Qiang explores disparities in transportation recovery…

Dan Qiang awarded Best Poster in TRB 2024 Session

January 11, 2024

Dan Qiang received the “Best Poster” award from the standing committee on public transportation planning and development at TRB2024…

Outstanding paper award at EMNLP2023

December 10, 2023

A new paper lead by lab member Mikael Brunila was recently awarded the Outstanding Paper Award at EMNLP2023…

Two presentations at TRB2024

November 1, 2023

Two doctoral students from the lab will attend and present at the 103rd Annual Meeting of the Transportation Research Board…

Best paper award at GIScience ’23

October 6, 2023

Our paper “Platial k-anonymity” was selected for the Best Full Paper award at this year’s GIScience conference…

Zhang, Hongyu; McKenzie, Grant

Geoprivacy knowledge, attitudes, and behaviours in contemporary China Journal Article

In: Geographical Review, 2024.

Abstract | Links | BibTeX

Qiang, Dan; McKenzie, Grant

Navigating the Post-Pandemic Urban Landscape: Disparities in Transportation Recovery & Regional Insights from New York City Journal Article

In: Computers, Environment and Urban Systems, vol. 110, pp. 102111, 2024.

Abstract | Links | BibTeX

Verma, Priyanka; McKenzie, Grant

Regional Comparison of Socio-Demographic Variation in Urban E-scooter Usage Journal Article

In: Environment and Planning B: Urban Analytics and City Science, 2024.

Abstract | Links | BibTeX

@article{Verma2024,

title = {Regional Comparison of Socio-Demographic Variation in Urban E-scooter Usage},

author = {Priyanka Verma and Grant McKenzie},

url = {https://grantmckenzie.com/academics/Verma_2024.pdf},

year  = {2024},

date = {2024-03-26},

urldate = {2024-03-09},

journal = {Environment and Planning B: Urban Analytics and City Science},

abstract = {In recent years we have witnessed explosive growth in the shared, free-floating, electric scooter industry. While still controversial in many North American cities, a number of large e-scooter operators have managed to carve out a piece of the urban transportation landscape. As these vehicles shift from novelty services to increasingly reliable modes of short personal travel, the discussion has turned to investigating who exactly benefits from these micromobility services and who are being left behind. Though population surveys have been administered to identify the socio-demographic characteristics of e-scooter riders in the past, little work has linked these characteristics through trips, or investigated the regional variation in these demographic factors. In this work we explore the variability and similarities in e-scooter rider characteristics across three major U.S. cities. To accomplish this, we apply a Moran’s Eigenvector Spatial Filtering linear regression model and compare our results to more commonly used spatial regression approaches. Our results indicate that the spatial filtering approach outperforms other methods in identifying socio-demographic characteristics of e-scooter users, across multiple regions. We find that many socio-demographics associated with e-scooter usage are regionally variant, despite younger users making up the core user base in all cities. There are variations in usage based on gender, income, and race across cities with Black and Hispanic populations remaining underserved. The implications of these findings are discussed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

Brunila, Mikael; LaViolette, Jack; CH-Wang, Sky; Verma, Priyanka; Féré, Clara; McKenzie, Grant

Toward a Critical Toponymy Framework for Named Entity Recognition: A Case Study of Airbnb in New York City Best Paper Proceedings Article

In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP2023), 2023.

Abstract | Links | BibTeX