Automated Sentiment Analysis for Issue Tracking
detail.loadingPreview
Leverage AI to automatically analyze the sentiment of your issue comments. This workflow extracts sentiment, summarizes conversations, and logs the analysis to Airtable for historical tracking.
About This Workflow
This n8n workflow empowers you to gain deeper insights into the sentiment surrounding your project's issues. By connecting to your issue tracking system and leveraging OpenAI's powerful language models, it automatically analyzes the sentiment expressed in issue comments. The workflow then extracts key sentiment attributes like overall sentiment and a conversational summary. Crucially, it integrates with Airtable to store and track this sentiment data over time, allowing you to identify trends, gauge community perception, and proactively address concerns. This provides a valuable layer of emotional intelligence to your issue management process.
Key Features
- AI-Powered Sentiment Analysis: Utilizes OpenAI to determine the sentiment (positive, negative, neutral) of issue comments.
- Conversational Summarization: Generates concise summaries of comment discussions.
- Intelligent Data Extraction: Extracts sentiment and summary directly from comment bodies.
- Airtable Integration: Seamlessly stores and retrieves sentiment data in Airtable for historical analysis.
- Historical Tracking: Records previous sentiment to identify changes and trends.
How To Use
- Connect Your Issue Source: Configure the initial node to pull issues from your source (e.g., GitHub, Jira – this snippet assumes a generic issue source).
- Split Issues: Use the 'Issues to List' node to process individual issues.
- Analyze Comment Sentiment: The 'Sentiment over Issue Comments' node processes the comments, extracting sentiment and a summary using OpenAI.
- Configure OpenAI Credentials: Ensure your OpenAI API key is set up in n8n.
- Combine Analysis: The 'Combine Sentiment Analysis' node merges the issue data with the sentiment results.
- Prepare for Airtable: The 'Copy of Issue' node prepares the combined data for Airtable insertion.
- Batch Processing: 'For Each Issue...' processes issues individually for Airtable operations.
- Fetch Existing Data: 'Get Existing Sentiment' retrieves previous sentiment records from Airtable using the Issue ID.
- Update Airtable: 'Update Row' inserts or updates the sentiment analysis record in your Airtable base, including current and previous sentiment, issue details, and the summary.
Apps Used
Workflow JSON
{
"id": "5426f007-641f-4929-a4cd-077038f1c38f",
"name": "Automated Sentiment Analysis for Issue Tracking",
"nodes": 15,
"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: 5426f007-641f...
About the Author
N8N_Community_Pick
Curator
Hand-picked high quality workflows from the global community.
Statistics
Related Workflows
Discover more workflows you might like
Automate Qualys Report Generation and Retrieval
Streamline your Qualys security reporting by automating the generation and retrieval of reports. This workflow ensures timely access to crucial security data without manual intervention.
Automated PR Merged QA Notifications
Streamline your QA process with this automated workflow that notifies your team upon successful Pull Request merges. Leverage AI and vector stores to enrich notifications and ensure seamless integration into your development pipeline.
Build a Custom OpenAI-Compatible LLM Proxy with n8n
This workflow transforms n8n into a powerful OpenAI-compatible API proxy, allowing you to centralize and customize how your applications interact with various Large Language Models. It enables a unified interface for diverse AI capabilities, including multimodal input handling and dynamic model routing.