Automated Sentiment Analysis for Issue Tracking
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Streamline your issue tracking by automatically analyzing the sentiment of comments using AI. This workflow extracts sentiment from issue discussions and stores it alongside issue details in Airtable for better insights.
About This Workflow
This workflow automates the process of understanding the sentiment within your issue tracking system. It begins by splitting out individual issues from a source (likely a project management tool). For each issue, it analyzes the sentiment of all associated comments using OpenAI's language models, providing a sentiment score (positive, negative, neutral) and a summary of the conversation. This sentiment data is then enriched with issue details and stored in an Airtable base. The workflow also checks for existing sentiment data in Airtable, allowing for tracking sentiment changes over time and providing a historical view. This enables teams to quickly gauge the overall mood of an issue and proactively address potential problems.
Key Features
- AI-Powered Sentiment Analysis: Leverages OpenAI to accurately determine the sentiment of issue comments.
- Automated Data Enrichment: Combines sentiment analysis with issue details (assignee, timestamps, title) for comprehensive tracking.
- Airtable Integration: Seamlessly stores and retrieves sentiment data in your preferred Airtable base.
- Historical Sentiment Tracking: Captures previous sentiment to monitor trends and changes over time.
- Comment Summarization: Provides concise summaries of the sentiment expressed in issue discussions.
How To Use
- Configure Issue Source: Connect your issue tracking system (e.g., GitHub, Jira) to provide the 'Issues to List' node with issue data.
- Set Up OpenAI Credentials: Authenticate with your OpenAI API key in the 'OpenAI Chat Model' node.
- Define Sentiment Extraction: Configure the 'Sentiment over Issue Comments' node to process the comments and extract sentiment and summaries.
- Configure Airtable Integration: Set up your Airtable Base and Table in the 'Get Existing Sentiment' and 'Update Row' nodes, mapping the correct fields.
- Map Issue Data: In the 'Copy of Issue' node, ensure all relevant issue fields are passed to subsequent nodes.
- Execute and Monitor: Run the workflow to automatically analyze and store sentiment data in Airtable.
Apps Used
Workflow JSON
{
"id": "efea7b65-3320-4fbe-b671-6bbd11f8f8c4",
"name": "Automated Sentiment Analysis for Issue Tracking",
"nodes": 20,
"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: efea7b65-3320...
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