Automated Tweet Sentiment Analysis and Alerting Pipeline

This robust ETL pipeline is designed to streamline social media monitoring and sentiment analysis. It begins by regularly polling Twitter for tweets containing the '#OnThisDay' hashtag. Each fetched tweet is then stored in a MongoDB collection. Subsequently, the text of these tweets undergoes sophisticated sentiment analysis via Google Cloud Natural Language, yielding sentiment scores and magnitude. This analyzed data is then augmented with the original tweet text and stored in a PostgreSQL database. Finally, a conditional check filters for tweets with a positive sentiment score, triggering an immediate notification on Slack, complete with the tweet's content and its sentiment.