A new wave of Network Science - from fantasy to applications
summary
Constructs social maps from raw text by tagging every sentence mention and turning characters into nodes and co-mentions into weighted edges, processing ~5 million characters of The Witcher to reveal communities that match storylines and earning coverage in Gamestar. Builds scene-level networks from Game of Thrones subtitles, computes centrality features and trains a support vector machine to predict character deaths with meaningful signal. Applies the same pipeline to corporate email and customer graphs, uses geodata like OpenStreetMap and TomTom for city-layer networks, and packages network visualizations as NFTs on SuperRare.
AI-written summary · about
chapters (5)
- 0:00Start
- 1:13A brief history of network scien
- 3:35The Witcher's social netwo
- 11:15Who dies next in the Game of Thrones?
- 24:37Networks are art
related talks
01h 27mNetwork Science, Game of Thrones and US Airports
01h 38mNetwork Science for Fun and Profit
01h 25mNetwork Science, Game of Thrones and US Airports
46mGraph Algorithms: Predict Real-World Behavior
24mHands-On Network Science
41mDemystifying Social Network Analysis (SNA)
43mVisualising networks
01h 26mBuilding an Interactive Network Graph to Understand Communities