Collect new tweets that match a keyword and log them into an Airtable table for easy review. Great for marketing and community teams that want quick social listening without manual copy and paste.

The flow runs on click. It searches Twitter for a chosen term with up to 100 results. Existing rows are pulled from Airtable. Two mapping steps shape the data so both sides share the same fields like Tweet, Tweet_id, and Likes. A compare step checks Tweet_id and keeps only items that are not already stored. Only new tweets are then added to Airtable. The result is a clean list with no duplicates and a simple count of likes for each post.

You will need a Twitter developer app and an Airtable base with fields named Tweet, Tweet_id, and Likes. Expect faster monitoring and fewer errors because each run only adds what is new. Use this for brand mentions, event tracking, or competitor watch. You can keep it on demand or later add a schedule trigger in n8n if you want it to run on a timer.

• On demand run with a manual trigger for safe, controlled updates
• Twitter search pulls up to 100 recent and popular tweets for a chosen keyword
• Airtable list reads current records from your target table
• Set nodes normalize fields to Tweet, Tweet_id, and Likes for easy comparison
• Merge step filters out records that already exist by comparing Tweet_id
• Airtable append adds only the new tweets to keep the table clean

• Reduce manual tweet collection from 30 minutes to 2 minutes per run
• Eliminate 100 percent of duplicate entries using Tweet_id matching
• Connect Twitter and Airtable seamlessly for one source of truth
• Handle up to 100 tweets per run and scale by raising the limit
• Improve data quality by standardizing fields for every record

1. Import the template into n8n: Create a new workflow in n8n > Click the three dots menu > Select 'Import from File' > Choose the downloaded JSON file.
2. You'll need accounts with Twitter and Airtable. See the Tools Required section above for links to create accounts with these services.
3. In Airtable, create or choose a base and table. Add fields named Tweet (long text), Tweet_id (single line text), and Likes (number). Using text for Tweet_id avoids number precision issues.
4. Open the Twitter node in n8n. In the 'Credential to connect with' dropdown, click 'Create new credential' and follow the on screen steps. In your Twitter developer portal, create an app and keys, then paste them into n8n as requested.
5. Open the Airtable nodes (list and append). In the 'Credential to connect with' dropdown, click 'Create new credential' and follow the on screen steps. Create a personal access token in your Airtable account and use it in n8n.
6. In the Twitter node, change the search term from the example to your brand or topic. Adjust the limit if needed and keep result type as mixed for balanced results.
7. In the get Airtable list node, select your base and table. Confirm it returns existing rows so duplicates can be filtered.
8. Open both Set nodes. Make sure they output the same field names: Tweet, Tweet_id, and Likes. Map values from Twitter data in the Twitter set step and from Airtable fields in the Airtable set step.
9. Open the Merge node. Confirm mode is removeKeyMatches and both key fields are Tweet_id. This ensures only fresh tweets pass through.
10. Run the workflow once. Check Airtable for new rows. Run it again with the same term to confirm no duplicates are added.
11. If no data appears, test the Twitter node alone to see results. If duplicates still show up, verify the Tweet_id field is text in Airtable and that both Set nodes output the same field names.
12. Optional: If you want automatic runs, add a Cron node as a trigger and connect it to the flow. Keep the manual trigger for testing only.