How to Automate Facebook Comment Sentiment Analysis with Make.com and OpenAI

Introduction

Managing your brand’s online reputation is time-consuming if you have to manually monitor every single Facebook comment. With Make.com and OpenAI, you can fully automate this process:

• Detect positive, negative, or neutral comments.
• Save structured data to Google Sheets for reporting.
• Instantly notify your team on Slack when a negative comment appears.

In this tutorial, we’ll build a no-code AI automation that does all of this in real time.

Tools You’ll Need

• Facebook Page (to monitor comments)
• Make.com account
• OpenAI API (for AI sentiment analysis)
• Google Sheets (for tracking comments)
• Slack (for team alerts)

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Step-by-Step Workflow in Make.com

1. Trigger: Watch Facebook Comments

• Module: Facebook Pages > Watch Comments
• This pulls every new comment on your chosen posts.

2. AI Analysis: OpenAI Prompt

• Module: OpenAI > Create a Completion (Prompt)
• Use this JSON-only prompt:

You are a strict JSON generator. 
Analyze the sentiment of the following Facebook comment and return ONLY valid JSON, no extra text. 
The JSON must have exactly two keys: "sentiment" and "summary". 
"sentiment" must be one of: Positive, Negative, Neutral. 
"summary" must be a one-sentence neutral summary of the comment. 
Comment: "{{message}}"

Example output:

{
  "sentiment": "Negative",
  "summary": "The user is unhappy with late delivery."
}

3. Parse JSON

• Module: Tools > Parse JSON
• Schema:

{
  "type": "object",
  "properties": {
    "sentiment": {
      "type": "string",
      "enum": ["Positive", "Negative", "Neutral"]
    },
    "summary": { "type": "string" }
  },
  "required": ["sentiment", "summary"]
}

This gives you two clean variables: sentiment and summary.

4. Save to Google Sheets

• Module: Google Sheets > Add a Row
• Columns: Date, Comment, Sentiment, Summary

5. Router: Branch Logic

• Positive → Google Sheets → Save for testimonials or marketing.
• Negative → Slack → Instant team alert.
• Neutral → Google Sheets → For future reference.

6. Slack Notification

• Module: Slack > Create Message
• Send the summary and original comment with a link to the post.

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Final Workflow Overview

Your finished automation will:

1. Monitor Facebook comments in real time.
2. Analyze sentiment using AI.
3. Save all results into Google Sheets.
4. Alert your team in Slack if negative sentiment is detected.

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Why This Matters

• Save hours of manual monitoring.
• Instant alerts help you act quickly on customer issues.
• Data-driven insights for marketing and support teams.