FAQ

Frequently asked questions about Social Analyzer

General Questions

What is Social Analyzer?

Social Analyzer is an API, CLI, and web application for analyzing and finding a person’s profile across 1000+ social media websites. It uses multiple detection techniques and a rating mechanism to identify profiles with varying levels of confidence (0-100%).

The tool is designed for OSINT (Open Source Intelligence) investigations and can help identify profiles related to suspicious or malicious activities such as cyberbullying, cyber grooming, cyberstalking, and spreading misinformation.

Is Social Analyzer free to use?

Yes, Social Analyzer is open source and free to use under the AGPL-3.0 license. The source code is available on GitHub at https://github.com/qeeqbox/social-analyzer.

Note that some law enforcement agencies use an enhanced detection database that differs from the public version.

How many social media platforms does it search?

Social Analyzer searches across 1000+ social media websites and platforms. You can view the complete list using:

python3 -m social-analyzer --list

The database includes major platforms like Twitter, Facebook, Instagram, GitHub, as well as hundreds of niche and regional sites.

What programming languages does Social Analyzer support?

Social Analyzer is available in:

• Python 3 (CLI and module)
• Node.js (CLI and web app)

You can use it as a command-line tool or import it as a module in your Python scripts.

Can I use Social Analyzer for commercial purposes?

Social Analyzer is licensed under AGPL-3.0, which requires that any derivative works or services using the code must also be open source. If you plan to use it commercially, review the license terms carefully or contact the author for alternative licensing arrangements.

Detection and Accuracy

How accurate is Social Analyzer?

Social Analyzer uses a rating mechanism that produces confidence scores from 0 to 100%:

• 0-33%: Low confidence (“No”)
• 34-66%: Medium confidence (“Maybe”)
• 67-100%: High confidence (“Yes”)

The detection system is designed to minimize false positives. Accuracy varies by website based on:

• Site structure and consistency
• Anti-bot protection measures
• Profile privacy settings
• Username availability and uniqueness

For best results, filter for “good” status profiles (high confidence matches).

What detection methods does Social Analyzer use?

Social Analyzer employs multiple detection techniques:

1. Normal Detection: Standard HTTP requests and HTML parsing
2. Advanced Detection: Selenium WebDriver for JavaScript-heavy sites
3. Special Detection: Custom logic for specific platforms (Facebook, Gmail, Google)
4. OCR Detection: Optical character recognition using Tesseract

You can select detection modes using the --mode flag:

• fast: FindUserProfilesFast (HTTP only)
• slow: FindUserProfilesSlow (includes WebDriver)
• special: FindUserProfilesSpecial (platform-specific methods)

Why do I get 'Maybe' results?

“Maybe” results (medium confidence) occur when:

• The username exists but the profile is private or restricted
• The page structure is ambiguous
• Anti-bot protections interfere with detection
• The username matches but additional verification is needed

To see only high-confidence results:

python3 -m social-analyzer --username "johndoe" --filter "good"

Manually verify “maybe” results by visiting the URLs directly.

Can Social Analyzer detect deleted or suspended accounts?

Generally no. Social Analyzer detects active, publicly accessible profiles. Deleted or suspended accounts typically return “not found” pages, which are filtered out.

However, you can:

• Use Wayback Machine integration to find archived profiles
• Check the failed results which might include recently deleted accounts
• Use specialized forensic tools for deleted content recovery

Usage and Features

What's the difference between fast and slow mode?

Fast Mode (--mode fast):

• Uses only HTTP requests (no browser automation)
• Faster execution (seconds to minutes)
• Lower resource usage
• May miss JavaScript-rendered content
• Best for quick scans of many users

Slow Mode (--mode slow):

• Uses Selenium WebDriver (browser automation)
• Slower execution (minutes to hours)
• Higher accuracy for modern web apps
• Captures JavaScript-rendered content
• Best for thorough investigation of specific users

How do I search for multiple usernames at once?

Separate usernames with commas (no spaces):

python3 -m social-analyzer --username "johndoe,janedoe,john_doe123"

This is useful for:

• Correlating multiple aliases of the same person
• Batch processing investigation lists
• Finding connections between accounts
• Testing username variations

What is metadata extraction?

Metadata extraction (--metadata flag) pulls additional information from detected profiles:

• Profile descriptions and bios
• Posted content snippets
• Profile images and avatars
• Account creation dates (when available)
• Location information
• Social connections (followers, following)

Usage:

python3 -m social-analyzer --username "johndoe" --metadata --extract

This feature uses the QeeqBox OSINT module for enhanced data collection.

Can I search only specific websites?

Yes, use the --websites parameter:

# Single site
python3 -m social-analyzer --username "johndoe" --websites "github"

# Multiple sites (space-separated)
python3 -m social-analyzer --username "johndoe" --websites "github twitter instagram"

This significantly speeds up searches when you know which platforms to target.

How do I export results for analysis?

Export results in JSON format:

python3 -m social-analyzer --username "johndoe" --output "json" > results.json

You can then:

• Import into spreadsheets (Excel, Google Sheets)
• Process with data analysis tools
• Integrate with other OSINT tools
• Store in databases
• Generate reports

See the Integration Guide for more examples.

Does Social Analyzer work with proxies?

Yes, you can configure proxy settings in the code by modifying the headers and session configuration. For custom proxy usage:

from importlib import import_module

SocialAnalyzer = import_module("social-analyzer").SocialAnalyzer()
SocialAnalyzer.headers = {
    "User-Agent": "Your-Custom-User-Agent"
}
# Add proxy configuration to session

Proxies are useful for:

• Avoiding rate limiting
• Bypassing geo-restrictions
• Distributing load
• Maintaining anonymity

Technical Questions

What are the system requirements?

Minimum Requirements:

• Python 3.6+ or Node.js 12+
• 2 GB RAM
• Internet connection
• 500 MB disk space

Recommended:

• Python 3.8+ or Node.js 14+
• 4 GB RAM
• SSD storage
• Stable internet connection

Optional Components:

• Firefox or Chrome (for screenshots and advanced detection)
• Tesseract OCR (for OCR-based detection)
• Docker (for containerized deployment)

Can I run Social Analyzer on a server without a GUI?

Yes, Social Analyzer works in headless environments. However:

• CLI mode: Works perfectly without GUI
• Screenshots: Require a display or virtual display (Xvfb)
• Advanced detection: May need headless browser configuration

For headless servers:

# Install virtual display
sudo apt-get install xvfb

# Run with virtual display
xvfb-run python3 -m social-analyzer --username "johndoe"

Alternatively, use Docker which handles headless configuration automatically.

How long does a typical search take?

Search time varies significantly based on:

Search Scope:

• All 1000+ sites: 10-30 minutes
• Top 100 sites: 2-5 minutes
• Specific sites: 10-60 seconds

Detection Mode:

• Fast mode: 50-200ms per site
• Slow mode: 2-10 seconds per site

Additional Features:

• Metadata extraction: +30-50%
• Screenshots: +100-200%

Optimization Tips:

• Use --top to limit site count
• Use --websites for specific targets
• Increase worker count (code modification)
• Use Docker grid mode for parallel processing

Does Social Analyzer store any data?

Social Analyzer itself does not maintain a persistent database of searches or results. However:

Data Storage:

• Logs are saved to temp directory if --logs flag is used
• Screenshots are saved locally if --screenshots flag is used
• JSON output is saved only if you redirect it to a file

Privacy Notes:

• No data is sent to external servers (except target websites)
• All processing is local
• You control all output and storage
• Clean up logs and screenshots after use

The tool is designed for local use, not as a service.

Can I add custom websites to the database?

Yes, you can modify the data/sites.json file to add new websites. Each entry requires:

{
  "url": "example.com",
  "selected": "false",
  "detections": [
    {
      "return": "true",
      "check": "username in page"
    }
  ]
}

However:

• Manual testing is required for each site
• Detection logic must be customized per site
• Anti-bot measures may affect success
• Consider contributing back to the main project

What's the difference between 'find' and 'get' methods?

The --method parameter controls result filtering:

find: Returns only detected profiles (positive matches)

python3 -m social-analyzer --username "johndoe" --method "find"

get: Returns all profiles regardless of detection status

python3 -m social-analyzer --username "johndoe" --method "get"

all: Combines both approaches (default behavior)

python3 -m social-analyzer --username "johndoe" --method "all"

Most users should use “find” or “all” for investigation purposes.

Legal and Ethical Questions

Is using Social Analyzer legal?

Using Social Analyzer to search public information is generally legal, but:

Legal Considerations:

• Only searches publicly accessible information
• Must comply with local laws and regulations
• Some jurisdictions have strict privacy laws
• Terms of service of target platforms may prohibit automated access

Recommended Usage:

• Law enforcement investigations
• Security research
• Personal reputation management
• Cybersecurity threat intelligence

Prohibited Usage:

• Harassment or stalking
• Identity theft
• Unauthorized surveillance
• Violating platform terms of service

Consult legal counsel if you’re unsure about your specific use case.

What are the ethical considerations?

When using Social Analyzer, consider:

Ethical Guidelines:

1. Only investigate with legitimate purpose
2. Respect privacy and personal boundaries
3. Handle discovered information responsibly
4. Don’t use for harassment or intimidation
5. Secure any collected data appropriately
6. Follow your organization’s ethics policies

Best Practices:

• Document your investigation purpose
• Obtain proper authorization when required
• Minimize data collection to what’s necessary
• Delete data when no longer needed
• Protect subject privacy in reports

Can I use this tool for background checks?

Social Analyzer can be used as part of background research, but:

Important Limitations:

• Cannot verify identity with certainty
• May find profiles of different people with same username
• Public profiles may not reflect current status
• Information may be outdated or inaccurate

Recommendations:

• Use as supplementary tool, not primary source
• Verify findings through multiple methods
• Comply with Fair Credit Reporting Act (US) if applicable
• Consider hiring professional background check services
• Always verify critical information independently

Troubleshooting

Why am I getting so many failed results?

Common reasons for failed results:

1. Network Issues: Check your internet connection
2. Rate Limiting: Websites blocking automated requests
3. Outdated Detections: Site structure changed since last update
4. Anti-Bot Protection: Cloudflare, CAPTCHA, etc.
5. Timeout Too Low: Increase with --timeout 15

Solutions:

# Filter to only show detected profiles
python3 -m social-analyzer --username "johndoe" --profiles "detected"

# Increase timeout
python3 -m social-analyzer --username "johndoe" --timeout 20

See the Troubleshooting Guide for detailed solutions.

What if I find a bug or issue?

If you encounter problems:

1. Check GitHub Issues: https://github.com/qeeqbox/social-analyzer/issues
2. Search for similar problems - may already be solved
3. Update to latest version:
   pip3 install --upgrade social-analyzer
   
4. Open a new issue with:
   • Operating system
   • Python/Node.js version
   • Complete error message
   • Steps to reproduce
   • Command you ran

Note: For private module issues, contact the author directly (don’t open GitHub issues).

Getting Help

Where can I get more help?

Resources:

• Documentation: https://github.com/qeeqbox/social-analyzer
• GitHub Issues: https://github.com/qeeqbox/social-analyzer/issues
• Wiki: https://github.com/qeeqbox/social-analyzer/wiki
• Examples: See the Usage Examples page
• Integration Guide: See Integration Guide

Community:

• Search existing GitHub issues
• Check closed issues for solutions
• Review pull requests for upcoming features

How can I contribute to the project?

Contributions are welcome!

Ways to Contribute:

• Report bugs and issues
• Suggest new features
• Add detection rules for new websites
• Improve documentation
• Submit pull requests with fixes
• Share usage examples and tutorials
• Test and provide feedback

Getting Started:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

See CONTRIBUTING.md in the repository for detailed guidelines.

Is there a commercial or enterprise version?

The standard version is open source and free. However:

• Some law enforcement agencies use an enhanced detection database
• The public version differs from the professional version
• For enterprise licensing or custom features, contact the author directly
• Private modules are available for specific use cases

Contact: [e-mail]