Classify sentiment of incoming text using Hugging Face, Google Sheets, and Jira

Sentiment Analysis Workflow using Webhook, Hugging Face, Google Sheets & Jira

This workflow automatically analyzes incoming text feedback, classifies it into Positive, Neutral or Negative using a Hugging Face sentiment model, stores results in Google Sheets and creates Jira tickets for negative feedback.

Quick Steps to Get Started

1. [Import the workflow into your n8n account](https://n8n.partnerlinks.io/om1efg2qgvwi) 2. Set up Webhook endpoint (/sentiment-input) 3. Add Hugging Face API token in HTTP Request node 4. Configure Google Sheets (3 tabs: Positive, Neutral, Negative) 5. Connect Jira credentials 6. Activate the workflow 7. Send POST request with text data

What It Does

This workflow automates sentiment analysis of incoming text data using a machine learning model hosted on Hugging Face. It receives multiple text inputs via a webhook, processes each input individually and evaluates sentiment scores returned by the model.

The workflow intelligently determines whether the sentiment is Positive, Neutral or Negative based on the highest score and a confidence threshold. It ensures more reliable classification by applying a score validation logic.

Once classified, the workflow routes the data accordingly. Each sentiment category is stored in a separate Google Sheets tab, making it easy to track and analyze feedback trends. Additionally, any negative feedback automatically triggers the creation of a Jira ticket, enabling quick issue resolution.