Much of my empirical work involves the use of computational methods, and I have long been interested in developing tools to help my fellow researchers. Below is an evolving list of the code I have used in my scholarly projects. I hope to see more researchers share their code in order to both increase the transparency of academic research and to promote scientific progress. As such, my code is typically licensed under permissive, copyleft licenses like the Mozilla Public License. All my code is available on Github. My current tools of choice are Python, R, and PHP.
- A Computational Approach for Examining the Comparability of 'Most-Viewed Lists' on Online News Sites (2017)
- On Metrics-Driven Homepages: Assessing the relationship between popularity and prominence (2016)
- Capturing and Analyzing Liquid Content: A computational process for freezing and analyzing mutable documents (2016)