How jumblewisp scores trust
Your Web of Trust
When you log in, jumblewisp builds a Web of Trust (WoT) from your social graph:
- 1 hop: everyone you follow
- 2 hops: everyone your follows follow
This gives you a pool of typically thousands of pubkeys — your extended network.
Two Signals
For any given account, we track two things:
- Follows — how many of your direct follows also follow them
- Mutes — how many people in your WoT have muted them
The Formula
We use Bayesian-smoothed exponential decay:
followRate = follows / myFollowSetSize muteRate = mutes / wotSize priorRate = 2%
smoothedRatio = (muteRate + priorRate × 10%) / (followRate + priorRate) score = round(100 × exp(−5 × smoothedRatio))
Dividing by myFollowSetSize means signal strength scales with your curation habits. If you follow 100 people, a single follow carries real weight. If you follow 10,000, it contributes far less — because mass-following is a weaker endorsement.
The prior keeps scores stable for accounts with little data. The exponential decay means even a small mute-to-follow ratio drops the score sharply.
What the Numbers Mean
| Situation | Score |
|---|---|
| Well-followed, never muted | ~87 |
| Unknown to your network | 1 |
| Muted by many, followed by none | 0 |
A score of 1 means the account is simply unknown — no one in your network follows or mutes them. A score of 0 means your WoT has actively flagged them with no countervailing follows.
Why This Approach
Your follow and mute graph is already a distributed reputation system — jumblewisp just does the math. No central authority decides who’s trustworthy. Your network does.
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