ABSTRACT
We discuss how computational social scientists can achieve high standards of accessibility, transparency, replicability, and reproducibility by adhering to four open science principles: open practices, open data, open tools, and open access. For each principle, we discuss the underlying motivation, challenges, and potential solutions for computational social scientists. Open practices refer to honest and transparent specification of all steps in the data processing and data analysis. We recommend that computational social scientists share their materials and analysis scripts. Open data refers to data that are publicly available, and we urge computational social scientists to share their data whenever possible. When data cannot be shared, researchers ought to be explicit about the conditions of its availability. Open tools refer to software that is both free and has its source code available to others. We recommend that computational social scientists share their code, software, and educational materials whenever possible so that other people can learn computational techniques. Finally, open access is making the products of one’s research process publicly available. We encourage computational social scientists to use open-access outlets for the ultimate publication of work when feasible and to self-archive their research products regardless.
