This workflow automates the process of analyzing the sentiment of comments on YouTube videos by integrating Google Sheets, OpenAI’s language model, and n8n automation. The main goal is to fetch YouTube video URLs from a Google Sheet, retrieve comments, analyze their sentiment, and store the results back in the sheet, enabling efficient sentiment monitoring over time.

The workflow begins with a manual trigger for testing, which activates the sequence. It checks for the next scheduled fetch time in Google Sheets to determine if a new fetch should be initiated. If the scheduled time indicates it’s due, the workflow retrieves video URLs from a Google Sheet. For each video URL, it fetches the latest comments via an HTTP request.

Once comments are retrieved, each comment is sent to OpenAI’s language model to analyze its sentiment. The sentiment results are then formatted appropriately and written back into the Google Sheet along with the comment data. After processing, the workflow updates the last fetch timestamp and schedules the next fetch time, ensuring periodic sentiment analysis.

This automation is ideal for social media managers, content creators, or researchers who want to monitor audience sentiment on YouTube videos efficiently. It ensures comments are analyzed without manual intervention and maintains a historical record of sentiment trends in Google Sheets.

Node Count	11 – 20 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.sentimentAnalysis, googleSheets, httpRequest, if, manualTrigger, noOp, set, splitOut, stickyNote