YouTube Comment Sentiment Analysis with Google Gemini AI and Google Sheets

This workflow automatically **collects all comments from a specified YouTube video and analyzes the sentiment of each comment using an AI model** (e.g., GPT, Claude, or Gemini). The sentiment (**Positive, Neutral, or Negative**), its strength, and confidence score are extracted and saved into a connected **Google Sheet** for easy access, reporting, and visualization. --- ### **Advantages:** **AI-Powered Sentiment Analysis** * Uses modern language models (LLMs) to categorize comments with high accuracy. **Ideal for YouTube Creators & Marketers** * Provides insights into audience perception of videos, campaigns, or products. **Real-Time Feedback Monitoring** * Quickly identify trends in viewer sentiment across large comment volumes. **Automatic Reporting** * Saves results in Google Sheets for easy sharing or dashboard integration. **Handles Pagination** * Automatically fetches all comments, even from multi-page videos. **No-Code Customization** * Easily adaptable to other platforms (e.g., TikTok, Instagram) or data sources. **Simple Setup** * Requires just a YouTube video ID and API key - no coding needed. **Loop and Update Logic** * Continuously updates sheet with new results, avoiding duplicate processing. **Modular Design** * Easy to expand (e.g., reply classification, toxic comment detection, translation). **Multi-Language Compatibility** * AI can be configured to analyze comments in different languages with minimal setup.  --- ### **How It Works** 1. **Trigger**: The workflow starts manually (When clicking "Test workflow") or can be scheduled. 2. **Fetch Comments**: The Get API Comments node retrieves comments from a YouTube video using the YouTube API. 3. **Process Comments**: - Extracts comments and replies via the Comments node. - Splits them into individual entries (Split comments). - Saves raw comments to Google Sheets (Save comments). 4. **Sentiment Analysis**: - Uses **Google Gemini AI** (or another model) to classify each comment as **Positive, Neutral, or Negative**. - Captures **strength** and **confidence** metrics for deeper insights. 5. **Update Results**: The Update sentiment node writes the analysis back to Google Sheets, marking processed rows. 6. **Pagination Handling**: Checks for multiple pages of comments (Multipage?) and loops until all are processed. --- ### **Set Up Steps** 1. **Prepare Google Sheet**: - Clone the template: [YouTube Comments Sheet](https://docs.google.com/spreadsheets/d/14lAY5CjoYHqqFODiLGg636Gqw4JwWqb2CX10E8ZS6Uo/edit). - Ensure columns exist: `VIDEO_ID`, `COMMENTS`, `SENTIMENT`, `STRENGTH`, `CONFIDENCE`, and `DONE` (tracking column). 2. **Configure YouTube API**: - Obtain a **YouTube API key** from [Google Developers Console](https://developers.google.com/youtube/registering_an_application). - Add it to the Get API Comments node under **Youtube Query Auth** (parameter: `key`). 3. **Set Video ID**: - Replace the default `xxxxxxxx` in the ID Video node with your target YouTube video ID. 4. **AI Integration**: - Ensure **Google Gemini API** credentials are configured in the Google Gemini node. 5. **Run the Workflow**: - Test manually or automate execution (e.g., hourly/daily) to analyze new comments. **Output**: A Google Sheet with categorized sentiments, enabling **trend analysis and audience engagement tracking**. --- ### **Need help customizing?** [Contact me](mailto:info@n3w.it) for consulting and support or add me on [Linkedin](https://www.linkedin.com/in/davideboizza/).