UNDERSTANDING TOPICS API IN THE WILD DUBIOUS USAGE AND STALE ADOPTION

This project implements a comprehensive web analytics platform designed to monitor and analyse the adoption of Google's Topics API across the global web ecosystem. As the digital advertising industry transitions from third-party cookies to privacy-preserving alternatives, understanding the real-world implementation of the Topics API becomes crucial for developers, researchers, and privacy advocates. The system features a full-stack MERN (MongoDB, Express.js, React.js, Node.js) architecture with a modern Tailwind CSS interface that enables automated crawling of thousands of websites to detect Topics API usage patterns. The platform incorporates role-based access control with distinct admin and user functionalities, allowing administrators to manage system operations while providing researchers with detailed analytics dashboards. Key technical implementations include a distributed web crawler using Puppeteer for automated website scanning, real-time data visualization charts showing adoption trends across different regions and categories, and comprehensive user management systems. The application tracks critical metrics including adoption rates, regional distribution, crawl success rates, and temporal trends, providing valuable insights into how this new privacy technology is being deployed in practice. This research tool addresses the gap in independent monitoring of Privacy Sandbox technologies, offering transparency into the transition from traditional tracking methods to privacy-focused alternatives. The platform serves as both a practical monitoring solution and a research instrument for studying the evolution of web privacy standards in the post-cookie era.

Keywords: Topics API, Privacy Sandbox, Web Privacy, Third-Party Cookies, Web Measurement, MERN Stack, Web Crawling.