~/talk

Why You Can't Sit With Us - Understanding Network Analysis in Python With Mean Girls

Talkat PyOhio 2015 · 2015-08-01..08-02· [data-visualization, python]
links:none on file
slides:none on file

Hand-built edge list of every spoken line in Mean Girls gets loaded from CSV into NetworkX and plotted with matplotlib using weighted edges and a spring layout. The full graph has ~92 nodes and 96 edges, 20 components with 13 isolates; Regina reaches 56 characters (~70%) within three hops. Removing Cady raises components from 24 to 30 and lowers average degree, demonstrating Cady’s broker role and very high betweenness centrality — the code reproduces and visualizes these effects.

AI-written summary · about

  1. 0:00Introduction
  2. 1:08Why network analysis?
  3. 2:20Tools and methodology
  4. 3:25Data collection
  5. 5:12Types of graphs
  6. 6:47Centrality metrics
  7. 8:31Directing and measuring
  8. 10:20Connectedness and brokers
  9. 12:00Scene analysis
  10. 17:39Full movie network
  11. 20:01Visualizing clusters
  12. 22:02Edge weights and layouts
  13. 25:23Regina George analysis
  14. 29:03Influence of Cady
  15. 31:12Simulation and brokers
  16. 35:15Q&A: Multi-graphs
  17. 37:22Q&A: Dynamic networks
  18. 39:31Q&A: Huge networks
  19. 41:16Case study: Glen Coco
  20. 45:08Conclusion
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