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Trust + Merit Analyzers

The forum's trust + merit systems are dense graphs. Looking at one user's trust tab tells you a fraction of the picture. Community-built analyzers let you see the structure — who trusts whom, who's giving merit to whom, where the influence concentrates.

Trust DAG visualizers

Several community projects render DefaultTrust + extended trust as an interactive graph:

  • Nodes = users
  • Edges = trust relationships (positive / negative)
  • Edge weight = volume of feedback exchanged

What you learn:

  • Who's actually in DT (vs. who claims to be)
  • Which DT members are most influential (most others trust them)
  • Where there are isolated trust clusters (sock-puppet rings often show as disconnected sub-graphs)
  • Which users have unusually one-sided trust relationships (red flag for collusion)

Merit-flow trackers

Similar visualization, applied to merit:

  • Who's giving merit to whom
  • Which active users distribute the most sMerit
  • Boards where merit concentrates (often a leading indicator of where high-quality content lives)
  • Users whose merit comes mostly from a single small group (often farm-pattern)

Practical uses

Do

  • +Before joining a campaign, check the manager's trust graph for healthy structure
  • +When evaluating a service provider, look at the dispersion of their positive trust (many sources = better than one cluster)
  • +Use merit-flow data to find active curators in your area of interest
  • +Cross-reference: a 'great' user with only one tight cluster of trust is suspicious

Don't

  • −Take graph data as ground truth — it's a snapshot, not real-time
  • −Use these tools to harass — same data accelerates doxxing
  • −Trust shallow analysis — read the actual feedback content, not just the graph

Reading a trust graph

Healthy patterns:

  • Diverse sources of positive trust (many DT members, many non-DT members)
  • Reasonable in/out ratio (a user who trusts others moderately as well as receives trust)
  • Long-running connections (multi-year edges)

Suspicious patterns:

  • All positive trust from accounts that all trust each other (closed loop)
  • Only outgoing or only incoming trust (one-way relationships at scale)
  • New cluster of trust suddenly appearing around an account being evaluated for an opportunity

Limitations

  • Graph tools reflect public trust feedback only; they can't see PM-level commitments
  • They reflect quantitative structure but not qualitative content
  • They're maintained by individuals — can break or get out of date
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