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Persistent Homology for Resource Coverage: A Case Study of Access to Polling Sites

delete2024-08-08
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OA
AI
A
Abigail Hickok *
B
Benjamin Jarman
M
Michael Johnson
J
Jiajie Luo
M
Mason A. Porter
DOI:10.1137/22M150410Xdelete
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Abstract

Abstract

En 中文
It is important to choose the geographical distributions of public resources in a fair and equitable manner. However, it is complicated to quantify the equity of such a distribution; important factors include distances to resource sites, availability of transportation, and ease of travel. We use persistent homology, which is a tool from topological data analysis, to study the availability and coverage of polling sites. The information from persistent homology allows us to infer holes in a distribution of polling sites. We analyze and compare the coverage of polling sites in Los Angeles County and five cities (Atlanta, Chicago, Jacksonville, New York City, and Salt Lake City), and we conclude that computation of persistent homology appears to be a reasonable approach to analyzing resource coverage.
Keywords:
persistent homology
topological data analysis
resource coverage
voting access

Journal

SIAM Review cover
SIAM Review
IF:
6.1
Papers:
888
Citations:
1.2W

Organization

C
Columbia University
Scholars:
7.1W
Papers: 6.4W
Citations: 262
U
university of california los angeles
Scholars:
5.3W
Papers: 4.2W
Citations: 86
University of California System cover
University of California System
Scholars:
37.2W
Papers: 33.6W
Citations: 6.6K
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