Automate Sentiment Analysis and Posting of Tweets
This workflow automates the collection of tweets, analyzes their sentiment, stores them in databases, and posts positive tweets to a Slack channel.
The workflow begins by scheduling a daily task to collect tweets using a specific hashtag. These tweets are stored in a MongoDB collection and analyzed for sentiment using Google Cloud Natural Language. The sentiment score and magnitude are extracted and stored in a Postgres database. Tweets with positive sentiment are then posted in a designated Slack channel, while those with negative sentiment are ignored.
- Platform
- n8n
- Category
- Data & Analytics
- Price
- $9.99
- Creator
- Priya Patel
- if
- set
- cron
- noOp
- slack
- mongoDb
- postgres
- googleCloudNaturalLanguage
How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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