Extract and analyze Facebook post comments with sentiment AI using Gemini

This workflow automates the process of collecting, analyzing, and storing Facebook post comments with AI-powered sentiment analysis about YOUR Facebook Page.

Typical Use Cases:

• Social media sentiment monitoring
• Brand reputation analysis
• Campaign performance evaluation
• Community management and moderation insights
• Reporting and analytics for marketing teams

Key Advantages

✅ 1. Full Automation

Eliminates manual work by automatically collecting and analyzing Facebook comments end-to-end.

✅ 2. AI-Powered Sentiment Analysis

Uses Google Gemini to accurately classify user sentiment, enabling deeper insights into audience perception and engagement.

✅ 3. Structured Data Storage

Saves results directly into Google Sheets, making the data easy to analyze, share, and visualize with dashboards or reports.

✅ 4. Duplicate-Safe Updates

The “append or update” logic ensures comments are not duplicated and can be refreshed if sentiment analysis changes.

✅ 5. Scalable and Robust

Pagination handling, batch processing, and wait nodes allow the workflow to scale to large volumes of comments without hitting API limits.

✅ 6. Modular Architecture

The use of sub-workflows makes the solution reusable and easy to integrate into larger automation pipelines (e.g. monitoring multiple posts or pages).

✅ 7. Flexible Triggering

Can be run manually for testing or automatically as part of a broader workflow ecosystem.

How it works

This workflow automates the process of fetching Facebook post comments, performing sentiment analysis on each comment, and storing the results in a Google Sheet. It operates in two modes:

1. Manual execution mode:

   • Starts with a Manual Trigger, where the user enters a Facebook Post ID.
   • The workflow fetches the post details, then retrieves all comments (including pagination).
   • It calls a separate "Facebook" workflow (via the Call 'Facebook' node) to process each comment batch through sentiment analysis and save results to Google Sheets.

2. Triggered execution mode:

   • Activated via the "When Executed by Another Workflow" trigger, receiving comment data directly.
   • It splits and batches the incoming comments, processes each through the sentiment analysis model (Google Gemini), and appends/updates records in Google Sheets.

Set up steps

1. Configure Facebook Graph API credentials:

   • Add your Facebook Graph API credentials to both "Get Fb Post" and "Get Fb comments" nodes.

2. Set up Google Gemini API credentials:

   • Configure the "Google Gemini Chat Model" node with valid Google PaLM/Gemini API credentials.

3. Prepare Google Sheet:

   • Ensure the Google Sheet exists and is accessible via the Google Sheets OAuth2 credentials.
   • The sheet should have (or will automatically create) columns: POST ID, COMMENT ID, COMMENT, SENTIMENT.

4. Configure the sub-workflow call:

   • Ensure the "Call 'Facebook'" node points to a valid, existing workflow that can process comment data.

5. Optional: Adjust batch and wait settings:

   • Modify the "Loop Over Items" node if different batch sizes are needed.
   • Adjust the "Wait" node delay if required to avoid rate limits.

6. Activate the workflow:

   • Toggle the workflow to active if scheduled or webhook execution is desired.
   • Test using the Manual Trigger with a sample Facebook Post ID.

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