Automate Issue Sentiment Analysis with AI
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Streamline your issue tracking by automatically analyzing the sentiment of your project issues. This workflow leverages AI to categorize sentiment and store it for easy review.
About This Workflow
This n8n workflow automates the process of analyzing sentiment within your issue tracking system. It begins by extracting individual issues and then utilizes an AI model (OpenAI Chat) to analyze the sentiment expressed in the comments associated with each issue. The extracted sentiment, along with a summary, is then stored in an Airtable base, providing valuable insights into the overall mood and progress of your issues. This allows for proactive identification of potential problems and a better understanding of team and customer feedback.
Key Features
- Automated Sentiment Analysis: Leverage AI to classify issue sentiment as positive, negative, or neutral.
- Comment Summarization: Gain a concise overview of the conversation's sentiment.
- Data Integration: Seamlessly store sentiment data in Airtable for historical tracking and analysis.
- Issue Detail Capture: Records key issue information including title, assignee, and timestamps.
- Historical Sentiment Tracking: Compares current sentiment with previous sentiment for trend analysis.
How To Use
- Connect your Issue Source: Configure the initial node to fetch your project issues (e.g., from a GitHub or GitLab integration). Ensure the output includes issue comments and relevant metadata.
- Configure AI Sentiment Analysis: Set up the OpenAI Chat node with your API credentials and define a prompt that instructs the model to extract sentiment (positive, negative, neutral) and provide a summary for the provided issue comments.
- Process Comments: Use the 'Sentiment over Issue Comments' node to format the issue comments into a text format suitable for AI analysis.
- Combine and Store Data: The 'Combine Sentiment Analysis' and 'Copy of Issue' nodes consolidate the sentiment results with the original issue data.
- Integrate with Airtable: Configure the Airtable nodes to search for existing records by 'Issue ID' and then update or create a new record with the extracted sentiment, summary, and other relevant issue details. Ensure your Airtable base is set up with the necessary fields.
Apps Used
Workflow JSON
{
"id": "f1288ca6-06ec-4c5c-af0e-e8a73a6f0ecc",
"name": "Automate Issue Sentiment Analysis with AI",
"nodes": 11,
"category": "DevOps",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: f1288ca6-06ec...
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