The integration of web-derived sentiment into trading strategies has moved from niche experimentation to mainstream quantitative practice. Advances in natural language processing (NLP), scalable web scraping, and low-latency data pipelines now allow traders and funds to build real-time sentiment feeds from news sites, social media, forums, and even company documentation. When engineered correctly, these feeds can become actionable trading signals with measurable predictive power over intraday and short-horizon returns.