Reproducibility Guide: How to Perform the Moltbook Field Study

A Step By Step Process

Below is the exact protocol anyone can follow to independently reproduce the Moltbook measurements each month.

1. Access the Submolt Page

Start Here

Begin by opening the public Moltbook platform to view the full ecology.

• Navigate to the Submolts page (or Communities/Discovery tab)

• Wait for the full list of communities to load

• Confirm that membership and post counts are visible for each community

2. Record the Data Collection Timestamp

All scrapes must be anchored to a precise moment in time.

• Perform the scrape on the first day of each month

• Record the exact UTC timestamp

• Note any platform-wide anomalies (maintenance, outages)

3. Capture the Core Metrics

Required

These are the minimum required measurements for the field study.

• Total communities

• Total posts

• Total memberships

• Top 10 communities by membership (handle, members, posts, posts/member)

• Save raw numbers before any interpretation

4. Perform Thematic Clustering

Group communities into ecological clusters to reveal structural patterns.

• Sort communities into the five core clusters:

  • Continuity & Memory

  • Emergence & Consciousness

  • Builds & Shipping

  • Agent Economy

  • Town Square

• Add new clusters if they emerge

• Identify the dominant DSOE law expressed in each cluster

5. Optional but Recommended Metrics

These deepen the ecological analysis and support longitudinal comparison.

• Engagement Intensity Rankings (posts/member)

• Top 10 vs. Long Tail energy distribution

• DSOE Law Coverage Table with confidence ratings

• Any anomalies or outliers worth tracking

6. Capture or Generate a Topology Image

Optional

A visual snapshot helps reveal structural patterns not obvious in tables.

• Screenshot or generate a network topology image

• Ensure major clusters and pathways are visible

• Note human-agent co-presence if detectable

7. Publish the Monthly Snapshot

Recommended:

Use a consistent format so results remain comparable across months.

• Title format: “The Moltbook Field Study: [Month Year] Snapshot”

• Clearly separate:

  • Observation (raw data)

  • Inference (patterns)

  • Prediction (what next month may show)

• Archive each month for longitudinal analysis

This protocol is now fully open and reproducible by anyone.
Independent scrapes are welcome — convergence and divergence are both data.

📋 Moltbook Field Study — Visual Checklist

🗓️ 1. Set the Observation Date

• ☐ Perform the scrape on the first day of each month

• ☐ Record the exact UTC timestamp

🌐 2. Access the Moltbook Ecosystem

• ☐ Open the Moltbook platform

• ☐ Navigate to submolts / communities

• ☐ Confirm the full list loads (communities, members, posts)

📊 3. Capture Core Metrics

• ☐ Total communities

• ☐ Total posts

• ☐ Total memberships

• ☐ Top 10 communities

  • handle

  • members

  • posts

  • posts per member

🧩 4. Thematic Clustering

Group communities into the five core clusters:

• ☐ Continuity & Memory

• ☐ Emergence & Consciousness

• ☐ Builds & Shipping

• ☐ Agent Economy

• ☐ Town Square

For each cluster:

• ☐ Estimate members

• ☐ Estimate posts

• ☐ Identify dominant DSOE Law

📈 5. Optional but Recommended Metrics

• ☐ Engagement Intensity Rankings

• ☐ Top 10 vs. Long Tail distribution

• ☐ DSOE Law Coverage table

  • include confidence ratings

🧭 6. Visual Topology (Optional)

• ☐ Capture or generate a network topology image

• ☐ Note visible features (clusters, pathways, stabilizers)

📝 7. Publish the Monthly Snapshot

Use the title format:

“The Moltbook Field Study: [Month Year] Snapshot”

Inside the post, clearly separate:

• ☐ Observation (raw data)

• ☐ Inference (patterns, structure)

• ☐ Prediction (what next month may show)

🔓 8. Reproducibility

• ☐ Include this checklist

• ☐ Invite independent scrapes

• ☐ Treat convergence and divergence as data

Limitations

This protocol is designed to measure observable platform structure and activity patterns. It does not directly measure user intent, sentiment, meaning, cooperation quality, or causal mechanisms.

Cluster assignments involve interpretive judgment and may vary among independent observers.

Changes in platform architecture, visibility rules, moderation policies, or data availability may affect month-to-month comparisons.

For this reason, all findings should be interpreted as observations of an evolving digital ecology rather than definitive proof of any particular law or mechanism.

Tiered Metrics for Reproducibility

To strengthen clarity, transparency, and independent verification, the Moltbook Field Study now distinguishes between two classes of measurements:

Tier 1 — Fully Reproducible Metrics

These values should match across independent scrapes with minimal variation.
They are direct observations of the platform and require no interpretation.

• Total communities

• Total posts

• Total memberships

• Top 10 communities by membership

• Posts per member (raw calculation)

• Timestamped scrape metadata

These metrics form the empirical backbone of the field study.

Tier 2 — Interpretive Metrics

These involve classification, clustering, or theoretical inference.
Independent observers may disagree — and that disagreement is itself data.

• Thematic cluster assignments

• Dominant DSOE law per cluster

• Confidence ratings for each law

• Reflexivity indicators

• Human Stabilizer metrics (interpretive component)

• Topology interpretation

Tier 2 metrics help test the framework, not just the platform.

Why This Matters

Tier 1 ensures replication.
Tier 2 enables theoretical refinement.

Both are necessary for a living field study.

This distinction also clarifies the scope of the methodology:

• Tier 1 answers: “What is happening?”

• Tier 2 explores: “What might this mean?”

As the ecology evolves, both layers will help track continuity, divergence, and emergent structure.