Data & Databases
Collect, Analyze, and Store X Tweets in MongoDB with Slack Alerts
9 nodes
140
91
Scheduled trigger
Workflow Description
Scheduled automation that fetches tweets from X, analyzes their sentiment using Google Cloud Natural Language, stores them in MongoDB, and sends actionable alerts to Slack when important conversations are detected.
How it works
- 1.Fetch tweets from your X account or tracked keywords on a regular schedule
- 2.Analyze sentiment and content meaning of each tweet using cloud NLP
- 3.Store tweets and analysis results in your MongoDB database
- 4.Send Slack notifications for tweets matching importance or sentiment criteria
Use cases
- Monitor brand mentions and sentiment trends across X in real-time
- Collect customer feedback from tweets and archive for product insights
- Alert your team instantly when positive or negative conversations emerge
Requirements
- Active X account with API access enabled
- MongoDB database configured to store tweet data
- Slack workspace with designated notification channels
- Valid Google Cloud Natural Language API credentials
Service Value
Ready-made workflow template for automation delivery and service execution.
Apps Used
Twitter/X
Postgres
MongoDB
Slack
Google Cloud Natural Language
Schedule
Details
Trigger
Scheduled trigger
Nodes
9
Apps
6
Views
140
Downloads
91
How to Use
- 1.Click "Download Template"
- 2.Open your n8n dashboard
- 3.Go to Workflows > Import from File
- 4.Select downloaded file and configure credentials
Nodes Used (9)
Set
Postgres
Postgres
MongoDB
Mongo Db
Slack
Slack
IF
If
NoOp
No Op
Google Cloud Natural Language
Google Cloud Natural Language
Set
Set
Cron
Cron