Data Mining
LinkedIn Data Scraping & Structuring
A project extracting professional profiles and connection data from LinkedIn using Selenium, converting information into structured JSON for analysis.
Project Objective
The initiative aimed to collect detailed LinkedIn profile information, including professional connections, job positions, and related metadata structured as JSON for easy analysis and internal system integration.
Technology Stack
Web scraping powered by Selenium with ChromeDriver for browser automation, Python with BeautifulSoup for data parsing and transformation, and structured JSON output format.
Challenges Addressed
Three main obstacles: CAPTCHA and anti-bot detection solved via human-like delays, rotating user-agents, and proxies; dynamic content loading managed through Selenium's JavaScript interaction; and handling large datasets efficiently while respecting rate limits.
Applications
Market research, competitive analysis, talent acquisition, HR insights, and networking strategy development.
Technologies Used
Key Results
- 10,000+ profiles scraped
- 50,000+ first-degree connections extracted
- ~1.2 GB structured data output
- 72-hour completion time
- 99.5% accuracy rate
Services Used
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