3D UFO Belief Contagion Network

Belief Contagion — Baseline (3D)

Transmission rate β 0.35

Recovery / skepticism rate γ 0.12

Network density (avg links) 6

Susceptible S

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Believers I

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Skeptics R

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R₀ = β/γ

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How it works

The baseline case of the belief-contagion family, in 3D: 70 nodes are scattered uniformly at random inside a sphere and linked by a plain Erdős–Rényi random graph — every pair of nodes gets an edge with the same fixed probability, so the wiring has no clusters, no hubs, no demographic structure at all. Node color encodes S/I/R state and travels visibly along the lit edges as the belief spreads, unlike the flat population chart in the 2D version of this simulator.

dS/dt = -βSI
dI/dt =  βSI - γI
dR/dt =  γI
R0 = β/γ

Per network step of length dt, each Believer (I) node converts each Susceptible (S) neighbor independently with probability 1-e^(-β·dt), and independently recovers to Skeptic (R) with probability 1-e^(-γ·dt) — the same discrete-time analogue of the SIR equations as the 2D chart, just rendered as a spreading network instead of aggregated into curves.

Transmission rate β — probability weight of each believer→susceptible edge firing per step; drag it up to watch infection light up edges faster.
Recovery rate γ — how quickly a glowing orange believer node cools to skeptic cyan.
Network density — expected edges per node in the Erdős–Rényi graph; low density leaves isolated pockets the belief can't reach, high density approaches a fully-mixed population.
Drag to orbit, scroll to zoom — watch how a single seed believer at the graph's best-connected node either fizzles out or floods the whole cloud, depending on R0.

Susceptible S Believers I Skeptics R

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