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🕸️ Friendship Paradox & Network Superspreaders

A 3D contact network where a handful of high-degree hub nodes disproportionately drive an information cascade — tune transmission rate, virality, hub count and simple vs complex contagion.

AI & Machine Learning3DAdvanced60 FPS

A 3D contact network where a handful of high-degree hub nodes carry an outsized share of the edges, letting a random early hit on a hub trigger a fast, near-exponential information cascade.

🔬 What It Demonstrates

An SI-style contagion model on a graph with a skewed degree distribution: infected hub nodes transmit faster and susceptible hubs catch on faster, producing the same dynamics behind real-world superspreading events.

🎮 How to Use

Tune transmission rate, virality and hub count, or flip on complex contagion to require multiple infected neighbors before a node converts. Watch nodes reached climb and compare mean degree to mean neighbor degree.

💡 Did You Know?

Scott Feld's 1991 friendship paradox proves that, on average, your friends have more friends than you — a pure sampling artifact of network structure that also explains why hubs dominate real contagion dynamics.

⚙ Under the hood

A 3D contact network where a handful of high-degree hub nodes disproportionately drive an information cascade — tune transmission rate, virality, hub count and simple vs complex contagion.

artificial intelligencenetwork analysissocial networksinformation flownode centralitycontagionThree.js

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install