A News Scraper built with Python, Selenium, and BeautifulSoup to extract headlines, full articles, authors, categories, and publish dates from multiple news websites. Automates content collection into structured JSON/CSV formats for research, market analysis, sentiment tracking, and AI dataset generation.
The News Scraper is built with Python, Selenium & BeautifulSoup to extract:
- Headlines & article summaries
- Full article content
- Authors, categories, & publish dates
- News from multiple sources (blogs, portals, aggregators) It automates browsing and delivers structured JSON/CSV outputs for market research, data pipelines, sentiment analysis, and AI training datasets.
| Feature | Description |
|---|---|
| Multi-Source Support | Scrape news from multiple outlets & categories |
| Headline Extraction | Collect titles, authors, and publishing dates |
| Full Content Parsing | Extract complete articles for deeper analysis |
| Human-Like Automation | Random delays, scrolling, pagination |
| Scalable Workflow | Collect 1000s of articles efficiently |
"The News Scraper transformed how we monitor global headlines. Our team collected 50,000+ articles across 20+ news sites in a single week, saving countless hours of manual curation!" — Digital Media Agency
"We integrated the scraper into our sentiment analysis pipeline. Data quality improved instantly, giving us real-time insights into politics, finance, and tech trends." — AI Research Lab
"Custom features like category-based scraping and multilingual support were implemented flawlessly. A must-have tool for content aggregation and media research." — Content Intelligence Platform
- 90% faster article collection compared to manual copy-paste
- 500k+ news articles processed across multiple sources
- 70% reduction in editorial research costs
- 10x scalability with automation workflows
- 98% accuracy in JSON/CSV structured exports
- Reliable uptime with cross-platform support
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📰 News Scraper – Professional News & Media Data Extraction System