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urban-highways

Urban highways are barriers to social ties: Open source data and code for the research paper

https://github.com/nerdsitu/urban-highways

Science Score: 49.0%

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    Found 1 DOI reference(s) in README
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    Links to: arxiv.org
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    Low similarity (8.2%) to scientific vocabulary

Keywords

geospatial-analysis highways segregation social-network-analysis street-networks urban-data-science
Last synced: 6 months ago · JSON representation

Repository

Urban highways are barriers to social ties: Open source data and code for the research paper

Basic Info
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  • Stars: 14
  • Watchers: 3
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Topics
geospatial-analysis highways segregation social-network-analysis street-networks urban-data-science
Created almost 2 years ago · Last pushed 12 months ago
Metadata Files
Readme License Citation

README.md

Urban highways are barriers to social ties

Highway splash image

Open source data and code for the research paper published in PNAS:

L.M. Aiello, A. Vybornova, S. Juhsz, M. Szell, E. Boknyi
Urban highways are barriers to social ties
PNAS 122(10), e2408937122 (2025)

No-paywall paper download: arxiv.org/abs/2404.11596

Luca Maria Aiello1,2, Anastassia Vybornova1, Sndor Juhsz3, Michael Szell1,2,3,4, Eszter Boknyi5

1 IT University of Copenhagen, Copenhagen, 2300, Denmark

2 Pioneer Centre for AI, Copenhagen, 1350, Denmark

3 Complexity Science Hub Vienna, Vienna, 1080, Austria

4 ISI Foundation, Turin, 10126, Italy

5 University of Amsterdam, Amsterdam, 1018WV, The Netherlands

Contents of the repository

  • /code/
    • 00_randomize_twitter.ipynb: code to generate random Twitter data (does not need to be re-run)
    • 01_workflow.ipynb: main workflow from paper
    • 02_plots_paper.ipynb: code to reproduce plots from paper
    • 03_regressions.R: code to reproduce regressions
    • 04a_naturalbarriers_create.ipynb: code that downloads natural barrier (railway and waterway) data from OpenStreetMap
    • 04b_naturalbarriers_explore.ipynb: notebook for manual exploration of natural barrier data
    • config.yml: workflow settings for workflow.ipynb
    • utils.py: helper functions for workflow
  • /data/
    • /twitter_dummy/ random twitter nodes and edges generated by code/randomize_twitter.ipynb
    • error_logs & /social_networks/ & /social_networks_null/ & /street_networks_simplified/: output of workflow_dummydata.ipynb
    • cbsacode.csv (list of 50 sample cities)
    • tract_ids.gpkg (unique census tract codes for all 50 cities)
    • /regressions/ all data necessary to reproduce regression results
  • /results/ & /results_walking/: output of 01_workflow.ipynb (test run for Chicago)
  • /plots/: output of 01_workflow.ipynb and 02_plots_paper.ipynb

Instructions

  1. Create conda environment:

conda env create -f highenv.yml conda activate highenv

  1. Update config.yml (details within config file)

  2. Run ./code/01_workflow.ipynb with conda environment highenv

  3. Run ./code/02_plots_paper.ipynb with conda environment highenv

Contact

Owner

  • Name: NERDS
  • Login: NERDSITU
  • Kind: organization
  • Location: Denmark

NEtworks, Data, and Society research group at ITU Copenhagen

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