YouTube Comment Sentiment Analyzer

This workflow is for anyone who wants to analyze YouTube comments for sentiment. It's useful for content creators, marketers, or researchers. This automation helps you understand public opinion about specific YouTube videos. It saves time by automatically fetching comments, analyzing sentiment, and storing the data. This means you don't have to manually go through comments or use separate tools. This workflow also makes sure you don't fetch comments too often. This avoids hitting API limits or getting duplicate data. This workflow automatically collects YouTube comments from a list of video URLs. It checks if it’s time to fetch new comments, then uses AI to find out if each comment is positive, neutral, or negative. Finally, it saves all this information into a Google Sheet. You will need to set up credentials for Google Sheets, YouTube Data API v3, and OpenAI. Your Google Sheet must have two tabs: one for video URLs with last and next fetch times, and another for storing the analyzed comments. You also need to confirm that you have set up credential for these services: Google Sheets, YouTube Data API v3, and OpenAI API Key. Your YouTube data API key will be used as a query parameter. Google Sheets account, YouTube Data API v3 key, and OpenAI API key. The Google Sheet needs to be set up with specific column headers for video URLs, fetch times, comment IDs, comments, author names, likes, replies, sentiment, and publish dates. You can change the trigger to run automatically on a schedule. You can also change the sentiment categories in the AI analysis or adjust the AI model used. You can also change the fetching frequency in the Google Sheet. You can also adjust the maxResults in the HTTP Request node to fetch more or fewer comments at a time. This changes how many comments the workflow gets from YouTube per run.