ETL pipeline for text processing

About This Workflow

What This Workflow Does

This ETL pipeline workflow automates the collection of tweets, text analysis, and storage in multiple databases, enabling users to streamline their market research and sentiment analysis processes. It collects tweets, stores them in MongoDB, analyzes their sentiment, inserts them into a Postgres database, and posts positive tweets to a designated platform. This workflow simplifies the text processing pipeline, saving time and effort.

Who Should Use This

This workflow is ideal for developers, marketers, and business owners involved in market research, sentiment analysis, or social media monitoring. It can help anyone looking to automate their text processing pipeline and gain valuable insights from social media data.

Key Features

• Collects tweets based on specified keywords and hashtags
• Stores tweets in MongoDB for further analysis
• Analyzes the sentiment of collected tweets using AI-powered tools
• Inserts analyzed tweets into a Postgres database for long-term storage
• Posts positive tweets to a designated platform for further engagement

How to Get Started

To use this workflow, simply import it into your n8n environment and customize the nodes to match your specific needs and database connections. Configure the workflow settings, such as keywords and hashtags, to collect the tweets you're interested in analyzing.