Computational methods in urban studies
URB-404
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credits : Gorden Cullen
Computational Methods in Urban Studies
CMUS will focus on acquiring insights into, engaging with, and modeling the processes that underpin the transformation of contemporary urban and rural societies. The course will integrate statistical techniques and critical urban theory in order to develop both socially and environmentally fair policies within the context of the climate crisis.
Please find below a description of the assessment during the semester and the schedule.
- GEN - Structure of assessment (File)
- GEN - Schedule (File)
- R - CMUS GitHub page (URL)
- R - Cheat Sheets (Folder)
- R - Data paper about the Panel Lémanique (File)
- R - Panel Lémanique questionnaires (Folder)
- R - Panel Lémanique info (opalr) (URL)
Week 1 - Introduction : What is CMUS?
This lecture will introduce students to the program and the content of CMUS.
The following topics will be covered :
The following topics will be covered :
- Critical Urban Studies
- Interdisciplinary and "social engineering"
- Reflexive Quantification
- Program of the Semester
- Evaluation Assessment
- Introduction to R
Week 2 - Practices : (social) Space Oddity
This lecture will further introduce students to social and environmental inequalities through the example of the system of automobility.
The following topics will be covered :
- Social classes and social inequalities (Bourdieu)
- Topological urban sociology (Wacquant)
- Social inequalities within the system of automobility
- (Un)sustainable car practices
- Geometric data analysis (R session)
- Week 2 - Slides (File)
- Week 2 - References (Folder)
- R - Geometric Data Analysis (GDAtools) (URL)
- R - Additional dataset (File)
Week 3 - Bank Holidays!
Week 4 - Practices : A Goofy Motor Mania
Week 5 - Space/Territory : You can't Build your Way out of Congestion
- Week 5 - Slides (File)
- Week 5 - References (Folder)
- R - Municipalities characteristics (1) (File)
- R - Municipalities characteristics (2) (File)
- R - Full ballots data (File)
- R - Whisper transcript (File)
- R - Webscrapping (URL)
- R - Whisper (URL)
- R - quanteda (URL)
- R - plot_ly (URL)
