Academic Belief Contagion Simulator 3D

Academic Network

Hub professors 6

Hub connectivity 28

Transmission probability 18%

Immunization

Believers

–

Spread rate

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Hub professors infected

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How it works

The 2D companion draws this network flat, top-down. Here the same scale-free graph is laid out in 3D space: hub professors sit as large spheres on an inner shell (the conference-circuit clique), and every peripheral professor is pulled outward along the average direction of the hubs it cites or collaborates with — so hub clusters are spatially visible, not just algebraically implied.

degree distribution:  P(k) ~ k^-γ        (γ ≈ 2–3 for real citation nets)
peripheral position:  dir = normalize(Σ hub_pos of its neighbor hubs)
per-contact infection: P(transmit) = p · dt        (SI model, no recovery)

Belief color spread — each node's material color lerps from cool blue-gray (susceptible) to warm orange (believer) the instant it's infected, so you can watch the color front race across hub-to-hub links almost immediately, then crawl slowly across the sparse peripheral shell.
Hub vs. random immunization — immunizing hubs (dashed dark rings) removes the network's few long-range shortcuts and the epidemic threshold effectively vanishes; immunizing the same count of random peripheral nodes barely dents the spread, because peripheral nodes carry almost none of the network's total connectivity. This asymmetry is the real result from scale-free network robustness research (Cohen, Erez, ben-Avraham & Havlin, 2000/2001).

Hub professor Peripheral professor Believer Immunized

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Academic Belief Contagion Simulator (3D)