The Facebook Group Member Extractor automates the process of collecting member information from public or authorized Facebook Groups on Android devices. It eliminates manual scrolling, tapping, and copying, providing clean structured data in minutes. This tool delivers consistent results for researchers, marketers, and automation engineers who need reliable group member insights.

This automation system simulates human interaction on Android to navigate Facebook’s group interface, open the members list, scroll through all available entries, and extract relevant member metadata. It removes repetitive data-collection tasks and ensures consistent, device-agnostic results. Businesses and analysts benefit from improved speed, accuracy, and operational reliability.

• Provides large-scale member data without manual effort.
• Ensures consistent capture across different device sizes and OS versions.
• Reduces human error through deterministic UI-automation flows.
• Enables rapid dataset generation for research, outreach, or analytics.
• Supports multi-device parallelization for higher throughput.

1. Input or Trigger — User provides Facebook credentials, group URL/ID, and extraction parameters.
2. Core Logic — The bot launches the Facebook app, navigates the UI, scrolls member lists, and captures visible data.
3. Output or Action — Extracted information is parsed and saved to JSON and CSV formats.
4. Other Functionalities — Optional queue-based scheduling, multi-device orchestration, and proxy rotation.
5. Safety Controls — Rate-limiting, UI validation, controlled scrolling speeds, and error-recovery loops.

Language: Python Frameworks: Appilot, UI Automator, FastAPI (optional for orchestration) Tools: ADB-less controllers, device farm schedulers, proxy rotation utilities Infrastructure: Local devices, cloud Android farms, containerized worker nodes

automation-bot/
├── src/
│   ├── main.py
│   ├── automation/
│   │   ├── tasks.py
│   │   ├── scheduler.py
│   │   └── utils/
│   │       ├── logger.py
│   │       ├── proxy_manager.py
│   │       └── config_loader.py
├── config/
│   ├── settings.yaml
│   ├── credentials.env
├── logs/
│   └── activity.log
├── output/
│   ├── results.json
│   └── report.csv
├── requirements.txt
└── README.md

• Researchers use it to collect demographic or behavioral data for analysis, so they can generate insights faster.
• Marketers use it to compile outreach lists, so they can improve targeted engagement.
• Business Owners use it to understand group composition, so they can refine community strategies.
• Automation Teams use it to populate datasets for machine learning or CRM pipelines.
• Agencies use it to perform repetitive extraction tasks at scale, so they can reduce operational overhead.

Does it require root access? No, it operates on standard Android devices using UI automation.

Can it extract private data? Only publicly visible or authorized information accessible from the logged-in account.

Is parallel operation supported? Yes, the scheduler allows multiple devices to run simultaneously.

Does the tool work with the Facebook Lite app? It is optimized for the main Facebook app but can be adapted.

How often can extraction be performed? As often as needed, depending on scheduling, rate limits, and device availability.

Execution Speed: Typically 120–200 member-card actions per minute on standard device farms. Success Rate: Approximately 93–94% across long-running jobs with retries and recovery enabled. Scalability: Supports 300–1,000 Android devices using sharded queues and horizontally scaled workers. Resource Efficiency: ~10–15% CPU and 250–350MB RAM per active worker per device. Error Handling: Auto-retries with exponential backoff, structured logs, alerting hooks, and graceful recovery on UI mismatches.