Automated Twitter Sentiment Analysis and Data Pipeline

This n8n workflow is designed to automate the process of monitoring Twitter for specific hashtags, analyzing the sentiment of the tweets, and then acting upon that analysis. It begins by scheduling a daily fetch of tweets containing the hashtag #OnThisDay. These tweets are then stored in MongoDB for initial processing. Following this, the Google Cloud Natural Language API is leveraged to determine the sentiment score and magnitude of each tweet's text. The workflow then enriches the tweet data with these sentiment metrics before storing them in a PostgreSQL database. Finally, an IF node checks if the sentiment score is positive, triggering a Slack notification if it is. This powerful automation can be customized to suit various social media listening and data integration needs.