YouTube Comment Sentiment Analyzer

YouTube Comment Sentiment Analyzer automates the collection and analysis of YouTube comments, categorizing sentiments as Positive, Neutral, or Negative. It fetches comments based on video URLs stored in Google Sheets, analyzes their sentiment using OpenAI, and updates the results back into the sheet. This workflow streamlines the process of understanding audience feedback, helping creators gauge viewer sentiment efficiently and effectively.

7/4/2025
16 nodes
Complex
manualcomplexsplitoutlangchainnoopgooglesheetssticky noteadvancedlogicconditionalapiintegration
Categories:
Data Processing & AnalysisManual TriggeredComplex Workflow
Integrations:
SplitOutLangChainNoOpGoogleSheetsSticky Note

Target Audience

This workflow is ideal for:
- Content Creators: Individuals or organizations creating YouTube videos who want to analyze viewer engagement through comments.
- Marketers: Professionals looking to gauge public sentiment about products or services based on YouTube comments.
- Researchers: Academics or analysts interested in studying trends in viewer opinions and feedback on video content.
- Social Media Managers: Those managing online communities who need to understand audience sentiment and engagement levels.

Problem Solved

This workflow addresses the challenge of efficiently analyzing YouTube comments for sentiment without manual effort. It automates the process of fetching comments, analyzing their sentiment using OpenAI, and storing the results in Google Sheets for easy access and further analysis. This eliminates the need for manual data collection and sentiment evaluation, saving time and providing insights into audience perceptions.

Workflow Steps

  • Manual Trigger: The workflow begins when the user clicks ‘Execute Workflow’.
    2. Fetch Video URLs: It retrieves a list of YouTube video URLs from Sheet2 in Google Sheets.
    3. Check Fetch Timing: The workflow checks if it's time to fetch new comments based on the last fetched timestamp.
    4. Get Comments: If the timing is right, it fetches comments for each video URL using the YouTube Data API.
    5. Analyze Sentiment: Each comment is then analyzed for sentiment (Positive, Neutral, Negative) using the OpenAI API.
    6. Format Data: The results are formatted to include essential details like comment ID, video URL, comment text, author name, likes, replies, sentiment, and published timestamp.
    7. Store Results: The formatted data is appended or updated in Sheet1 of Google Sheets.
    8. Update Fetch Timing: Finally, the workflow updates the last fetched time and the next fetch time in Sheet2 to ensure timely future executions.

    • Customization Guide

    Users can customize this workflow by:
    - Modifying the Sheets: Adjust the structure of Sheet1 and Sheet2 to fit specific data requirements, such as adding or removing columns.
    - Changing the Sentiment Analysis Model: Update the OpenAI model used for sentiment analysis to a different version or type if needed.
    - Adjusting Fetch Frequency: Modify the logic that determines the frequency of comment fetching by changing the timing conditions in the workflow.
    - Integrating Additional APIs: Users can enhance the workflow by integrating other APIs for more comprehensive data analysis or reporting.
    - Adding Notifications: Implement notification nodes to alert users when the workflow completes or encounters errors.