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Computational reproducibility in computational social science

David Schoch, Chung-hong Chan, Claudia Wagner, Arnim Bleier · EPJ Data Science · 2024

AbstractOpen science practices have been widely discussed and have been implemented with varying success in different disciplines. We argue that computational-x disciplines such as computational social science, are also susceptible to the symptoms of the crises, but in terms of reproducibility. We expand the binary definition of reproducibility into a tier system which allows increasing levels of reproducibility based on external verifiability to counteract the practice of open-washing. We provide solutions for barriers in Computational Social Science that hinder researchers from obtaining the highest level of reproducibility, including the use of alternate data sources and considering reproducibility proactively.

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