Platial Analysis Lab

Platial Lab at AAG 2023

April 4, 2023

Two members of the lab attended the American Association of Geographers annual meeting in Denver, CO this year…

The 4th Spatial Data Science Symposium

March 23, 2023

This year the lab will be heavily involved in organizing the 4th Spatial Data Science Symposium with a hub at McGill University…

Platial Lab at SKI2023

February 20, 2023

Last week six members of the lab participated in the 8th conference on Spatial Knowledge and Information (SKI) Canada…

New “Idea to Innovation” grant from NSERC

February 2, 2023

The lab was recently awarded a grant from the Natural Sciences and Engineering Research Council of Canada’s (NSERC) Idea to Innovation program…

“NLP for Social Science” workshop series

January 25, 2023

In collaboration with Columbia University, the Platial Analysis Lab is co-organizing a workshop on Natural Language Processing for Social Science…

MixMap presentation at AutoCarto 2022

December 30, 2022

The video of co-author Sarah Battersby (Tableau Research) presenting our MixMap AutoCarto paper is available online…

Axe throwing with the Platial Analysis Lab

December 4, 2022

Working hard and playing hard at the lab holiday event…

Spatial Knowledge and Information Conference

October 11, 2022

We are co-organizing the 8th conference on spatial information and knowledge (SKI) Canada in Banff, AB next year…

The lab welcomes two new graduate students

August 28, 2022

A warm welcome to Doctoral student Dan Qiang and Master’s student Clara Féré…

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