Scrape Twitter Profiles with Bright Data API and Export to Google Sheets

🐦 Twitter Profile Scraper via Bright Data API with Google Sheets Output

A comprehensive n8n automation that scrapes Twitter profile data using Bright Data's Twitter dataset and stores comprehensive tweet analytics, user metrics, and engagement data directly into Google Sheets.

📋 Overview

This workflow provides an automated Twitter data collection solution that extracts profile information and tweet data from specified Twitter accounts within custom date ranges. Perfect for social media analytics, competitor research, brand monitoring, and content strategy analysis.

✨ Key Features

🔗 Form-Based Input: Easy-to-use form for Twitter URL and date range selection
🐦 Twitter Integration: Uses Bright Data's Twitter dataset for accurate data extraction
📊 Comprehensive Data: Captures tweets, engagement metrics, and profile information
📈 Google Sheets Storage: Automatically stores all data in organized spreadsheet format
🔄 Progress Monitoring: Real-time status tracking with automatic retry mechanisms
⚡ Fast & Reliable: Professional scraping with built-in error handling
📅 Date Range Control: Flexible time period selection for targeted data collection
🎯 Customizable Fields: Advanced data field selection and mapping

🎯 What This Workflow Does

Input Twitter Profile URL**: Target Twitter account for data scraping Date Range**: Start and end dates for tweet collection period Custom Fields**: Configurable data points to extract

Processing Form Trigger: Collects Twitter URL and date range from user input API Request: Sends scraping request to Bright Data with specified parameters Progress Monitoring: Continuously checks scraping job status until completion Data Retrieval: Downloads complete dataset when scraping is finished Data Processing: Formats and structures extracted information Sheet Integration: Automatically populates Google Sheets with organized data

Output Data Points

| Field | Description | Example | |-------|-------------|---------| | user_posted | Username who posted the tweet | @elonmusk | | name | Display name of the user | Elon Musk | | description | Tweet content/text | "Exciting updates coming soon..." | | date_posted | When the tweet was posted | 2025-01-15T10:30:00Z | | likes | Number of likes on the tweet | 1,234 | | reposts | Number of retweets | 567 | | replies | Number of replies | 89 | | views | Total view count | 12,345 | | followers | User's follower count | 50M | | following | Users they follow | 123 | | is_verified | Verification status | true/false | | hashtags | Hashtags used in tweet | #AI #Technology | | photos | Image URLs in tweet | image1.jpg, image2.jpg | | videos | Video content URLs | video1.mp4 | | user_id | Unique user identifier | 12345678 | | timestamp | Data extraction timestamp | 2025-01-15T11:00:00Z |

🚀 Setup Instructions

Prerequisites n8n instance (self-hosted or cloud) Bright Data account with Twitter dataset access Google account with Sheets access Valid Twitter profile URLs to scrape 10-15 minutes for setup

Step 1: Import the Workflow Copy the JSON workflow code from the provided file In n8n: Workflows → + Add workflow → Import from JSON Paste JSON and click Import

Step 2: Configure Bright Data Set up Bright Data credentials: In n8n: Credentials → + Add credential → HTTP Header Auth Enter your Bright Data API credentials Test the connection Configure dataset: Ensure you have access to Twitter dataset (gd_lwxkxvnf1cynvib9co) Verify dataset permissions in Bright Data dashboard

Step 3: Configure Google Sheets Integration Create a Google Sheet: Go to Google Sheets Create a new spreadsheet named "Twitter Data" or similar Copy the Sheet ID from URL: https://docs.google.com/spreadsheets/d/SHEET_ID_HERE/edit Set up Google Sheets credentials: In n8n: Credentials → + Add credential → Google Sheets OAuth2 API Complete OAuth setup and test connection Prepare your data sheet with columns: Use the column headers from the data points table above The workflow will automatically populate these fields

Step 4: Update Workflow Settings Update Bright Data nodes: Open "🚀 Trigger Twitter Scraping" node Replace BRIGHT_DATA_API_KEY with your actual API token Verify dataset ID is correct Update Google Sheets node: Open "📊 Store Twitter Data in Google Sheet" node Replace YOUR_GOOGLE_SHEET_ID with your Sheet ID Select your Google Sheets credential Choose the correct sheet/tab name

Step 5: Test & Activate Add test data: Use the form trigger to input a Twitter profile URL Set a small date range for testing (e.g., last 7 days) Test the workflow: Submit the form to trigger the workflow Monitor progress in n8n execution logs Verify data appears in Google Sheet Check all expected columns are populated

📖 Usage Guide

Running the Workflow Access the workflow form trigger URL (available when workflow is active) Enter the Twitter profile URL you want to scrape Set the start and end dates for tweet collection Submit the form to initiate scraping Monitor progress - the workflow will automatically check status every minute Once complete, data will appear in your Google Sheet

Understanding the Data Your Google Sheet will show: Real-time tweet data** for the specified date range User engagement metrics** (likes, replies, retweets, views) Profile information** (followers, following, verification status) Content details** (hashtags, media URLs, quoted tweets) Timestamps** for each tweet and data extraction

Customizing Date Ranges Recent data**: Use last 7-30 days for current activity analysis Historical analysis**: Select specific months or quarters for trend analysis Event tracking**: Focus on specific date ranges around events or campaigns Comparative studies**: Use consistent time periods across different profiles

🔧 Customization Options

Modifying Data Fields Edit the custom_output_fields array in the "🚀 Trigger Twitter Scraping" node to add or remove data points:

"custom_output_fields": [ "id", "user_posted", "name", "description", "date_posted", "likes", "reposts", "replies", "views", "hashtags", "followers", "is_verified" ]

Changing Google Sheet Structure Modify the column mapping in the "📊 Store Twitter Data in Google Sheet" node to match your preferred sheet layout and add custom formulas or calculations.

Adding Multiple Recipients To process multiple Twitter profiles: Modify the form to accept multiple URLs Add a loop node to process each URL separately Implement delays between requests to respect rate limits

🚨 Troubleshooting

Common Issues & Solutions

"Bright Data connection failed" Cause: Invalid API credentials or dataset access Solution: Verify credentials in Bright Data dashboard, check dataset permissions

"No data extracted" Cause: Invalid Twitter URLs or private/protected accounts Solution: Verify URLs are valid public Twitter profiles, test with different accounts

"Google Sheets permission denied" Cause: Incorrect credentials or sheet permissions Solution: Re-authenticate Google Sheets, check sheet sharing settings

"Workflow timeout" Cause: Large date ranges or high-volume accounts Solution: Use smaller date ranges, implement pagination for high-volume accounts

"Progress monitoring stuck" Cause: Scraping job failed or API issues Solution: Check Bright Data dashboard for job status, restart workflow if needed

Advanced Troubleshooting Check execution logs in n8n for detailed error messages Test individual nodes by running them separately Verify data formats and ensure consistent field mapping Monitor rate limits if scraping multiple profiles consecutively Add error handling and implement retry logic for robust operation

📊 Use Cases & Examples

1. Social Media Analytics Goal: Track engagement metrics and content performance Monitor tweet engagement rates over time Analyze hashtag effectiveness and reach Track follower growth and audience interaction Generate weekly/monthly performance reports

2. Competitor Research Goal: Monitor competitor social media activity Track competitor posting frequency and timing Analyze competitor content themes and strategies Monitor competitor engagement and audience response Identify trending topics and hashtags in your industry

3. Brand Monitoring Goal: Track brand mentions and sentiment analysis Monitor specific Twitter accounts for brand mentions Track hashtag campaigns and user-generated content Analyze sentiment trends and audience feedback Identify influencers and brand advocates

4. Content Strategy Development Goal: Analyze successful content patterns Identify high-performing tweet formats and topics Track optimal posting times and frequencies Analyze hashtag performance and reach Study audience engagement patterns

5. Market Research Goal: Collect social media data for market analysis Gather consumer opinions and feedback Track industry trends and discussions Monitor product launches and market reactions Support product development with social insights

⚙ Advanced Configuration

Batch Processing Multiple Profiles To monitor multiple Twitter accounts efficiently: Create a master sheet with profile URLs and date ranges Add a loop node to process each profile separately Implement delays between requests to respect rate limits Use separate sheets or tabs for different profiles

Adding Data Analysis Enhance the workflow with analytical capabilities: Create additional sheets for processed data and insights Add formulas to calculate engagement rates and trends Implement data visualization with charts and graphs Generate automated reports and summaries

Integration with Business Tools Connect the workflow to your existing systems: CRM Integration**: Update customer records with social media data Slack Notifications**: Send alerts when data collection is complete Database Storage**: Store data in PostgreSQL/MySQL for advanced analysis BI Tools**: Connect to Tableau/Power BI for comprehensive visualization

📈 Performance & Limits

Expected Performance Single profile**: 30 seconds to 5 minutes (depending on date range) Data accuracy**: 95%+ for public Twitter profiles Success rate**: 90%+ for accessible accounts Daily capacity**: 10-50 profiles (depends on rate limits and data volume)

Resource Usage Memory**: ~200MB per execution Storage**: Minimal (data stored in Google Sheets) API calls**: 1 Bright Data call + multiple Google Sheets calls per profile Bandwidth**: ~5-10MB per profile scraped Execution time**: 2-10 minutes for typical date ranges

Scaling Considerations Rate limiting**: Add delays for high-volume scraping Error handling**: Implement retry logic for failed requests Data validation**: Add checks for malformed or missing data Monitoring**: Track success/failure rates over time Cost optimization**: Monitor API usage to control costs

🤝 Support & Community

Getting Help n8n Community Forum**: community.n8n.io Documentation**: docs.n8n.io Bright Data Support**: Contact through your dashboard GitHub Issues**: Report bugs and feature requests

Contributing Share improvements with the community Report issues and suggest enhancements Create variations for specific use cases Document best practices and lessons learned

📋 Quick Setup Checklist

Before You Start ☐ n8n instance running (self-hosted or cloud)
☐ Bright Data account with Twitter dataset access
☐ Google account with Sheets access
☐ Valid Twitter profile URLs ready for scraping
☐ 10-15 minutes available for setup

Setup Steps ☐ Import Workflow - Copy JSON and import to n8n
☐ Configure Bright Data - Set up API credentials and test
☐ Create Google Sheet - New sheet with proper column structure
☐ Set up Google Sheets credentials - OAuth setup and test
☐ Update workflow settings - Replace API keys and sheet IDs
☐ Test with sample data - Add 1 Twitter URL and small date range
☐ Verify data flow - Check data appears in Google Sheet correctly
☐ Activate workflow - Enable form trigger for production use

Ready to Use! 🎉

Your workflow URL: Access form trigger when workflow is active

🎯 Happy Twitter Scraping! This workflow provides a solid foundation for automated Twitter data collection. Customize it to fit your specific social media analytics and research needs.

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