Two papers in upcoming symposia

November 30, 2021

Papers published by lab members were recently accepted into two upcoming symposia this December.

A short peer-reviewed paper entitled “Data Horror”: Mapping (Spatial) Data Privacy Violations onto a Cognitive Account of Horror lead by Master’s student Daniel Romm with contributions by Hongyu Zhang, Priyanka Verma, Grant McKenzie, and Emily Chen was accepted to the The 2nd Spatial Data Science Symposium. The event will take place December 13-14 online and is completely free. Register here.

A short peer-reviewed paper entitled Leveraging Place Reviews to Identify the Affects of COVID-19 on Canadian Tourism by Grant McKenzie was accepted to the Third International Symposium on Platial Data Science. Lab members, Hongyu Zhang and Grant McKenzie are also organizing a mini-workshop during this event related to Cyber Ethics in Platial Research. This symposium will take place December 15-17 online and almost free. Register here.

Abstracts for the two papers:

“Data Horror'”: Mapping (Spatial) Data Privacy Violations onto a Cognitive Account of Horror

by Daniel Romm, Hongyu Zhang, Priyanka Verma, Grant McKenzie, Emily Chen

While spatial data privacy is not a new concern, recent information technology developments that allow for the increased collection and alternative use of spatial data have brought the discussion about geoprivacy back in focus. In this work, we draw a parallel between a conceptualization of horror based on work from cognitive scientists and philosophers, and the intrusiveness of current data collection methods, the unauthorized use of this data, and the transgressions made by data stewards. By drawing this connection, we discuss the familiar topic of data privacy through a novel lens that clarifies the importance of data privacy and elucidates the particular importance of geoprivacy.

Leveraging Place Reviews to Identify the Affects of COVID-19 on Canadian Tourism

by Grant McKenzie

The emergence of the COVID-19 pandemic disrupted travel world-wide and substantially impacted tourism in most countries. Though many governmental agencies and tourism boards have published data on the impact of the pandemic, in Canada, the vast majority of these data are reported at the national level or sparsely within individual regions. In this preliminary work, we leverage user-contributed tourist attraction reviews to better understand the nuanced changes in travel behavior resulting from the COVID-19 pandemic. We examine the regional impacts as well as the affects on different categories of tourism within Canada. The purpose of this short paper is to demonstrate the value of analyzing place-based user-generated tourism data and highlight some of the ways it can be leveraged by policy experts and tourism agencies.

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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

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}

}