SOCIAL MEDIA

Turn Angry Creator Mentions Into Linear Issues With Full Context

Detects negative mentions from high-reach creators and opens a prioritized Linear issue containing the conversation transcript, follower count, and a suggested reply draft.

CategorySocial Media
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerScheduled mention + follower scrapeApify
  • ActionClassify sentiment and draft replyOpenAI
  • LogicFilter negative + high-reach creators
  • LogicSet priority from severity and reach
  • OutputCreate assigned Linear issue with contextLinearLinear

What it does

Catches negative brand mentions, filters for accounts with meaningful reach, and creates a tracked Linear issue for each one. Each issue carries the full conversation, the creator's follower count, and an AI-drafted response so an owner can act and the work is auditable.

When to use it

When your team treats reputation risk like real work that belongs in a tracker, not a chat that scrolls away. Ideal for routing influential unhappy creators to a named owner with SLA-style priority.

How it works

  1. 1On a schedule, an Apify actor pulls recent mentions and the author's follower count.
  2. 2OpenAI classifies sentiment and, for negative ones, drafts a calm suggested reply.
  3. 3A branch keeps only negative mentions from accounts above a follower threshold.
  4. 4Issue priority is set from severity and reach so the loudest, largest accounts rise to the top.
  5. 5A Linear issue is created with the transcript, author stats, link, and draft reply, assigned to the reputation owner.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ApifyActors, scrapers, datasets.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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