A 30-Day Social Media Migration Experiment: Move a Learning Community from Reddit to Digg

Feeling stuck choosing platforms? Run a 30-day migration experiment from Reddit to Digg — with daily tasks, metrics, and templates.

If you manage a study group, you already know the pain: too many platform choices, falling participation, and the constant worry that moderation or algorithm changes will derail months of learning momentum. This guide gives you a pragmatic, evidence-informed 30-day experiment to move an active student community from Reddit to Digg in 2026 — designed to test engagement, moderation friction, and actual learning outcomes.

Why try this now (2026 context)

Late 2025 and early 2026 brought meaningful changes to the social platform landscape. Digg relaunched broadly, removed paywalls, and expanded community analytics and onboarding (ZDNET coverage in Jan 2026 noted the public beta and paywall removal). At the same time, organizers and educators have searched for reliable Reddit alternatives as Reddit’s API and policy shifts encouraged migrations in previous years.

That makes 2026 the right moment to run a controlled migration experiment. Digg today offers easier signups, cleaner moderation tooling, and early AI moderation helpers — features that are particularly useful for learning groups that need low-friction, predictable behavior from their platform.

What this experiment tests

• Engagement: Do posts, comments, and study sprints keep the same momentum after migrating?
• Moderation friction: How many moderator-hours are required, and how does report handling differ?
• Learning outcomes: Are study completion rates, peer teaching sessions, and pre/post quiz scores better, worse, or the same?

Core hypotheses (examples to adapt)

• H1: Daily active users (DAU) will fall by up to 30% in week 1 but recover to ≥80% of original DAU by day 30 with active seeding.
• H2: Moderator hours/week will drop or remain the same on Digg due to better moderation tooling, reducing friction for volunteer mods.
• H3: Structured learning activities (weekly sprints, micro-assessments) will improve measurable learning outcomes by a small but meaningful margin (e.g., +10% completion) among engaged members.

Before you begin: ethical and practical prerequisites

1. Get explicit consent from community members to migrate or offer an opt-in alternative. Transparent communication reduces churn.
2. Export community resources from Reddit (sidebars, pinned posts, any public documents) and back up moderation logs if allowed by Reddit rules.
3. Create a migration calendar and recruit a moderation team for Digg: aim for 3–5 initial volunteers for a 50–500 member group.
4. Set up measurement tools before migration: spreadsheets, Google Forms for quizzes/surveys, and a simple analytics log to track DAU, posts, comments and time-on-task.
5. Prepare a rollback plan: keep the Reddit community active but converted to read-only or archived if you need to reacclimate members.

Experiment overview: metrics to track

Track these daily and summarize weekly. Use a single spreadsheet or a simple dashboard.

• Engagement metrics
  • DAU and WAU (Daily/Weekly Active Users)
  • New posts/day, comments/post, average votes/post
  • Retention: Day-7 and Day-30 retention of users who visit in the first week
  • Time-on-task for synchronous study sprints (minutes per session)
• Moderation metrics
  • Moderator hours/week
  • Number of reports and removals/week
  • Average time-to-resolution for reports
  • Number of appeals or disputes
• Learning outcome metrics
  • Completion rate for weekly tasks (percent of active members completing)
  • Pre/post quiz score changes (average % improvement)
  • Peer instruction events held and attendance
  • Self-reported learning confidence (weekly survey)

30-Day day-by-day plan (high level)

Days 0–3: Preparation & soft-launch

• Day 0: Finalize migration announcement, publish migration timeline to Reddit with clear opt-in instructions and date for full transition.
• Day 1: Create the Digg community. Set up basic structure: channels (if Digg supports categorization in 2026) or clear tags, community rules, pinned syllabus and weekly calendar.
• Day 2: Post a warm welcome message and migrate key resources. Seed with 5–10 evergreen posts (syllabus, FAQ, study schedule, sample problems).
• Day 3: Invite mods and test moderation tools and automations; run a moderator orientation.

Days 4–10: Onboarding & seeding

• Day 4: Announce the first study sprint on Digg at a scheduled time. Use the pinned post to set expectations.
• Days 5–7: Host three onboarding events: a welcome AMA, a quick tutorial video on how to use Digg, and a moderated Q&A about rules.
• Day 8: Run the first pre-test (short quiz) to capture baseline learning metrics.
• Days 9–10: Promote cross-posts in Reddit pointing to Digg, and send reminder DMs or Emails to members who opted-in.

Days 11–20: Growth and A/B testing

• Days 11–12: Launch two A/B tests: A) content format (long-form guide vs. micro-thread) B) CTA types (weekly challenge vs. daily prompt).
• Days 13–16: Run mid-experiment surveys on ease-of-use, moderation satisfaction, and perceived learning value.
• Days 17–20: Scale moderator shifts and test an AI-moderation assistant (where available) to measure moderation-hours saved.

Days 21–27: Deep learning push

• Day 21: Launch a capstone mini-project with a 7-day deadline (peer-review required).
• Days 22–25: Organize structured peer-teaching sessions; track attendance and outcomes.
• Day 26: Run the post-test quiz and compare scores with pre-test.
• Day 27: Collect in-depth qualitative feedback (open-ended responses on what helped and what hurt learning).

Days 28–30: Wrap-up & analysis

• Day 28: Clean and export analytics; prepare charts for key metrics (DAU, retention, moderator hours, completion rates).
• Day 29: Moderator retro: document process, pain points, and wins.
• Day 30: Publish a transparent experiment report to the community with findings and a recommendation to stay, improve, or return.

Daily task checklist (copyable)

• Check moderation queue (30 mins)
• Seed at least one study prompt or reply to 5 member threads (15–30 mins)
• Post a reminder for any scheduled sprints/events (5–10 mins)
• Record key metrics for the day in the experiment spreadsheet (5–10 mins)
• Respond to onboarding questions from new members (15–30 mins)

Copy-ready templates

Migration announcement (Reddit post)

Hi everyone — we’re running a 30-day experiment to move our study group to Digg to test engagement and moderation tools. This is optional: our Reddit home will remain open for now. If you’d like to join the Digg space and help test, click here [Digg link] and reply “I’m in.” We’ll start seeding content on DATE and run our first study sprint on DATE. Questions? Ask below.

Welcome post (Digg)

Welcome! This community is an experiment: a 30-day migration from Reddit to test how Digg supports student learning. Read the pinned syllabus, introduce yourself (name, study goal, timezone), and join our first sprint on DATE & TIME. Our rules: be kind, stay on topic, and tag posts with the task tag. Questions → ask @moderator.

Study sprint prompt (template)

Sprint: 45-minute focused study on [Topic]. Goal: complete exercises 1–5 and post one question. Timer: 45 mins. Strategy: 25 min focused work + 10 min review + 10 min discussion. Reply with ✅ when you start and share one key learning when you finish.

Moderator shift template

Shift date: ______ Moderator: ______ Expected time commitment: 30–60 mins Tasks: check reports, approve flagged posts, welcome new members, enforce rule #2 (on-topic posts), log moderator hours.

Measurement plan: how to analyze results

At minimum, run three analyses:

1. Engagement trend lines: plot DAU, posts/day, comments/post weekly. Look for recovery patterns and change-points after major actions (e.g., onboarding event).
2. Retention cohorts: create cohort tables for users who visited in week 1 and check Day-7 and Day-30 retention percentages.
3. Learning effect size: compute average pre/post quiz score changes and use a paired t-test (or nonparametric equivalent) if sample sizes permit. Report mean difference and confidence intervals.

Common friction points and mitigation

• Initial drop in activity: anticipate and seed content heavily for week 1. Use direct outreach (DMs) for top contributors.
• Notification overload: provide a short guide on Digg notification settings; schedule digest posts instead of frequent pings.
• Cross-posting split: discourage multi-posting by clarifying canonical content locations and linking to archived Reddit threads.
• Moderation disagreements: keep an appeals channel and record decisions publicly to build trust.

Data privacy & compliance

Ask for consent when capturing identifiable learning data (quiz answers tied to users). If you use third-party analytics or AI moderation, document what data is shared and with whom. In 2026, platforms like Digg have added clearer privacy controls — use them to limit retention and export only what you need for the experiment.

Advanced strategies & 2026 trends to leverage

• AI moderation assistants: Trial built-in AI flags for low-effort moderation and compare time savings. Log false positive rates as a moderation quality metric.
• Structured micro-learning: Use short, repeatable daily prompts (3–5 minute micro-tasks) and measure cumulative learning across weeks.
• Cross-platform bridging: Maintain a low-traffic RSS or newsletter for members who prefer email, reducing platform lock-in.
• Federated identity & SSO: If Digg supports federated logins or SSO integrations in 2026, use these to lower signup friction and reduce churn.

Possible outcomes & decisions at day 30

At the end of 30 days, you'll likely land in one of three places:

• Stay on Digg — engagement matches or exceeds Reddit, moderation workload is manageable, and learning outcomes improved.
• Hybrid model — keep an archival presence on Reddit and active community on Digg for members who prefer each platform.
• Return or pivot — if engagement and learning drop significantly, analyze root causes and either iterate or return to Reddit with recommendations.

Sample short case (hypothetical)

Imagine a 120-member calculus study group. After seeding, Digg DAU dropped 40% in week 1, but targeted onboarding and daily sprints restored 75% of original DAU by day 21. Moderator hours fell from 12 to 8 per week after enabling AI-assisted flagging. Completion of weekly problem sets increased from 48% to 61% among active members by Day 30. These hypothetical numbers illustrate the patterns to expect and which levers to pull.

Quick troubleshooting checklist

• Low signups? Post short how-to videos and offer onboarding incentives (badges or recognition).
• Declining engagement? Run a one-day event with prizes and ask members to invite a friend.
• Moderator burnout? Shorten shifts and rotate responsibilities; automate low-risk tasks.

Final tips from seasoned community organizers

• Be transparent. Share analytics and decisions openly — transparency builds retention.
• Start small. Migrate core contributors first and scale outward.
• Measure learning, not just activity. Posts and likes are proxies; pre/post quizzes and completion rates show whether learning actually improved.

Resources & templates (copy & paste)

Use the templates above directly. Keep one editable, shared migration spreadsheet with tabs: Raw metrics, Moderator log, Pre/Post quizzes, Surveys, and Retention cohorts.

Call to action

Ready to run this experiment? Start today by announcing the migration plan to your Reddit group and scheduling your first Digg onboarding event. Try the 30-day playbook, record the metrics listed here, and share your experiment report back to the community of experimenters — we want to learn what worked for student communities in 2026. If you’d like, copy the templates in this guide and paste them into your community now.

Start the 30-Day Migration Challenge: pick day 0, invite your moderators, and commit to the data. Tag your results with #30DayMigration and let's build better learning spaces together.