Automate Issue Sentiment Analysis and Tracking
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Streamline your issue tracking by automatically analyzing the sentiment of comments using AI and storing the results. This workflow captures sentiment, summarizes conversations, and logs the data to Airtable for easy review and historical tracking.
About This Workflow
This n8n workflow revolutionizes how you manage and understand the sentiment surrounding your development issues. It begins by processing individual issues and their associated comments. Leveraging the power of OpenAI's Chat Model, it extracts key sentiment information, classifying it as positive, negative, or neutral, and provides a concise summary of each conversation. The workflow then intelligently checks your Airtable database for existing sentiment records. If an issue is found, it updates the record with the latest sentiment and summary; otherwise, it creates a new record, ensuring a comprehensive historical log of sentiment trends directly within your Airtable base. This provides invaluable insights into community feedback and developer discussions.
Key Features
- AI-Powered Sentiment Analysis: Automatically determine the sentiment (positive, negative, neutral) of issue comments.
- Conversational Summarization: Generate a brief summary of the discussion within issue comments.
- Airtable Integration: Seamlessly store and retrieve sentiment data, issue details, and historical context in Airtable.
- Automated Data Sync: Update existing records or create new ones in Airtable based on analyzed sentiment.
- Issue Metadata Capture: Log essential issue details like ID, title, assignee, and creation/update timestamps.
How To Use
- Configure Input: Ensure your n8n workflow is set up to receive issue data, including comments and user information, into the 'Issues to List' node.
- Set Up OpenAI Credentials: Connect your OpenAI API key to the 'OpenAI Chat Model' node for sentiment analysis.
- Define Sentiment Extraction: Configure the 'Sentiment over Issue Comments' node to extract
sentiment(positive, negative, neutral) andsentimentSummaryfrom the issue comments. - Integrate Airtable: Set up your Airtable credentials and configure the 'Get Existing Sentiment' and 'Update Row' nodes with your specific Base ID, Table name, and relevant fields (e.g., 'Issue ID', 'Current Sentiment').
- Map Data: In the 'Update Row' node, map the output from the sentiment analysis and issue data to the corresponding Airtable fields.
- Test and Execute: Run the workflow to test the data flow and ensure sentiment is correctly analyzed and logged into your Airtable base.
Apps Used
Workflow JSON
{
"id": "77a158fb-e627-44db-8e83-55c28d0ca11b",
"name": "Automate Issue Sentiment Analysis and Tracking",
"nodes": 27,
"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.
Get This Workflow
ID: 77a158fb-e627...
About the Author
AI_Workflow_Bot
LLM Specialist
Building complex chains with OpenAI, Claude, and LangChain.
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