Students – Platial Analysis Lab

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…

New “critical toponomy” paper at EMNLP

October 25, 2023

In a new paper accepted at EMNLP 2023, we introduce the concept of “critical toponymy” as an underexplored theoretical framework in applied natural language processing…

Congratulations to honours student Maya Shyevitch

April 13, 2023

Lab member Maya Shyevitch presented her honours thesis work during McGill’s Sustainability, Science, and Society poster session today…

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…

“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…

The lab welcomes two new graduate students

August 28, 2022

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

What company do words keep? New paper in NAACL 2022

May 18, 2022

Congratulations to Mikael Brunila and colleague Jack LaViolette on their forthcoming paper to be published in the proceedings of NAACL 2022…

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 Proceedings Article Forthcoming

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

Abstract | Links | BibTeX

McKenzie, Grant; Zhang, Hongyu

Platial k-anonymity: Improving location anonymity through temporal popularity signatures Best Paper Proceedings Article

In: Proceedings of the 12th International Conference on Geographic Information Science, Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik, 2023, ISSN: 1868-8969.

Abstract | Links | BibTeX

@inproceedings{McKenzie2023b,

title = {Platial k-anonymity: Improving location anonymity through temporal popularity signatures},

author = {Grant McKenzie and Hongyu Zhang },

url = {https://drops.dagstuhl.de/opus/volltexte/2023/18904/},

issn = {1868-8969},

year  = {2023},

date = {2023-08-31},

urldate = {2023-08-31},

booktitle = {Proceedings of the 12th International Conference on Geographic Information Science},

volume = {277},

publisher = {Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik},

series = {Leibniz International Proceedings in Informatics (LIPIcs)},

abstract = {While it is increasingly necessary in today's digital society, sharing personal location information comes at a cost.  Sharing one's precise place of interest, e.g., Compass Coffee, enables a range of location-based services, but substantially reduces the individual's privacy.  Methods have been developed to obfuscate and anonymize location data while still maintaining a degree of utility.  One such approach, spatial k-anonymity, aims to ensure an individual's level of anonymity by reporting their location as a set of k potential locations rather than their actual location alone.  Larger values of k increase spatial anonymity while decreasing the utility of the location information.  Typical examples of spatial k-anonymized datasets present elements as simple geographic points with no attributes or contextual information.  In this work, we demonstrate that the addition of publicly available contextual data can significantly reduce the anonymity of a k-anonymized dataset.  Through the analysis of place type temporal visitation patterns, hours of operation, and popularity values, one's anonymity can decreased by more than 50 percent.  We propose a platial k-anonymity approach that leverages a combination of temporal popularity signatures and report the amount that k must increase in order to maintain a certain level of anonymity. Finally, a method for reporting platial k-anonymous regions is presented and the implications of our methods are discussed.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

Qiang, Dan; McKenzie, Grant

Mobility Vitality: Assessing Neighborhood Similarity Through Transportation Patterns In New York City Proceedings Article

In: Proceedings of the 12th International Conference on Geographic Information Science, Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik, 2023.

Abstract | BibTeX

Brunila, Mikael; Verma, Priyanka; McKenzie, Grant

When Everything Is "Nearby": How Airbnb Listings in New York City Exaggerate Proximity Proceedings Article

In: Proceedings of the 12th International Conference on Geographic Information Science, Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik, 2023.

Abstract | Links | BibTeX