OpenWPM: An automated platform for web privacy measurement

Web measurement techniques have been highly influential in online privacy debates and have brought transparency to the online tracking ecosystem. Due to its complexity, however, web privacy measurement remains a specialized research field. Our aim in this work is transform it into a widely available tool. First, we analyze over 30 web privacy measurement studies, identify several methodological challenges for the experimenter, and discuss how to address them. Next, we present the design and implementation of OpenWPM, a flexible, modular web privacy measurement platform that can handle any experiment that maps to a general framework. It supports parallelism for speed and scale, automatic recovery from failures of the underlying browser, and realistic simulation of users. OpenWPM is open-source and has already been used as the basis of several published studies on web privacy and security. We show how our generic platform provides a common foundation for these diverse experiments, including a new study on the “filter bubble” which we present here.