Live exploration of Wikipedia editing dynamics with visual analytics: WhoColor and Interactive Wikipedia Article Analysis Notebooks

Abstract

The revision histories of Wikipedia articles are a rich source of data about the interactions of editors with each other and with the content, yet they are not straightforward to mine or understand. We describe two tools for visual analytics that support this effort: (i) An interactive browser extension to study word authorship, age, and conflict dynamics, which provides an overlay on live Wikipedia articles; and (ii) a novel interactive Jupyter Notebook package that allows us to run analyses of editorial dynamics out-of-the-box and is easily modifiable. Both leverage live data for any article on demand from several Web APIs, centering on our own WikiWho service, providing the most accurate mining of live word-level changes currently available. We show how these tools enable the exploration of the survival of content, productivity of editors, conflict dynamics, and other metrics through low-barrier interfaces while providing the opportunity for more quantitative investigations via access to the notebooks’ underlying data structures.