ETL pipeline for text processing
Explore this Workflow. Built for next generation AI app & agent building.
This workflow automates the collection, storage, analysis, and sharing of tweets. It collects tweets, stores them in MongoDB, analyzes their sentiment, inserts the data into a Postgres database, and posts positively rated tweets to a Slack channel.
Workflow Components:
- Cron Node: Schedules the workflow to run daily.
- Twitter Node: Collects tweets based on specified criteria.
- MongoDB Node: Stores collected tweets in MongoDB.
- Google Cloud Natural Language Node: Analyzes the sentiment of each tweet.
- Set Node: Extracts sentiment score and magnitude from analysis results.
- Postgres Node: Inserts tweets along with their sentiment score and magnitude into a Postgres database.
- IF Node: Filters tweets based on positive or negative sentiment scores.
- Slack Node: Posts tweets with positive sentiment to a designated Slack channel.
- NoOp Node: Ignores tweets with negative sentiment scores.
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