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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: 8 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 about 2 years ago · Last pushed about 1 year 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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