Description
Streamline your daily text data operations with this automated ETL pipeline in n8n. Designed to fetch tweets, store them, analyze sentiment, and share insights, this workflow bridges raw text and actionable intelligence—automatically.
🧠 How It Works:
✅ 🕒 Cron Trigger – Schedules the workflow to run daily at a set time ✅ 🐦 Twitter Node – Collects fresh tweets based on keywords or handles ✅ 🗂️ MongoDB Node – Stores raw tweets for historical and analytical purposes ✅ 🧠 Google Cloud NLP – Analyzes the sentiment of each tweet using advanced NLP ✅ 🛠️ Set Node – Extracts and formats sentiment score and magnitude ✅ 🛢️ Postgres Node – Inserts tweet content and sentiment data into a PostgreSQL database ✅ 🧪 IF Node – Filters tweets based on whether their sentiment is positive or negative ✅ 💬 Slack Node – Posts only positive tweets into a selected Slack channel ✅ 🚫 NoOp Node – Ignores tweets with negative sentiment (no further action)
🔍 It Automates:
✅ Tweet collection and storage in MongoDB ✅ Sentiment analysis via Google Cloud Natural Language API ✅ Data normalization and transformation ✅ Structured insertion into PostgreSQL for reporting ✅ Real-time Slack sharing of positive tweets ✅ Filtering of negative content automatically
💡 Why Choose This Workflow:
✅ End-to-end automated ETL with built-in analytics ✅ No manual tweet analysis or filtering required ✅ Dual-database architecture for raw and processed storage ✅ Keeps your team updated with only uplifting content ✅ Can be extended to include dashboards, alerts, or visualizations
👤 Who Is This For:
✅ Data analysts tracking brand sentiment ✅ Social media managers and marketing teams ✅ Developers building NLP-driven pipelines ✅ Anyone managing tweet-based text workflows
🔗 Integrations:
✅ Twitter API (via credentials) ✅ MongoDB (for raw tweet archiving) ✅ Google Cloud Natural Language (for sentiment scoring) ✅ PostgreSQL (for structured analytics) ✅ Slack (for real-time positive content alerts)
🔧 Setup Instructions:
🕒 Configure your desired schedule in the Cron Node 🔑 Set up Twitter API credentials in the Twitter Node 💾 Connect to MongoDB and PostgreSQL with proper credentials 🧠 Enable Google Cloud Natural Language API and link key 📈 Tune the sentiment thresholds in the IF Node as per your preference 📬 Add your Slack Webhook URL or workspace connection
📊 From Raw Text to Actionable Sentiment – Fully Automated This pipeline turns unstructured tweets into structured, sentiment-tagged records while highlighting positivity in real time. Build better strategies and stay ahead of audience sentiment—daily, effortlessly.
Link : https://lovable.dev/projects/aaeb9c0b-6369-4519-ade9-a019cb3c4c32
