Content Virality Cascade Simulator

Post Format

Content Strategy

Hook strength (first 3s) 55

Hashtag / discovery reach 40

Posting time 19:00

Ready to publish. Creator node is live.

Cascade Metrics

Reach

1 / 64 (1.6%)

Viral K-factor

0.00

Edge success rate

Cascade round

0 / 20

How it works

The audience is modelled as a follower graph: one creator, 9 direct followers, and 54 second-degree followers, plus a handful of cross-community "hashtag bridge" edges that jump between otherwise unconnected follower clusters. Spread follows the independent cascade model from network-diffusion theory (Kempe–Kleinberg–Tardos): each newly-activated node gets exactly one chance to activate each still-inactive neighbour, succeeding with probability p on that edge.

p(edge) = base(edge) · format · hook · time · hashtag
base = 0.16 (follower edge)  or  0.05 (bridge edge)
format  ∈ {0.7 text, 1.0 image, 1.15 carousel, 1.4 video}
hook    = 0.5 + 1.5 · (hookStrength / 100)
time    = 0.55 + 0.45 · cos(2π(hour−19)/24)   — peaks ~19:00
hashtag = 1 + 0.6·(reach/100)     on follower edges
        = 0.25 + 2.75·(reach/100) on bridge edges

Each simulation round, every node on the current "frontier" attempts its untried edges once; successes light up new nodes and become next round's frontier. This repeats until the frontier empties or 20 rounds pass — exactly how a real share cascade dies out once it runs out of receptive neighbours.

Reach — fraction of the 64-node audience ever activated.
Viral K-factor — successful activation attempts per activated node, the same metric growth teams use to tell whether a post is compounding (K>1) or fizzling (K<1).
Hashtag / discovery reach mainly amplifies the rare bridge edges — it decides whether the post escapes the creator's own network into a new community.

Creator Reached (direct) Reached (extended) Not yet reached

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