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The workshop advances computational reproducibility in social science research involving behavioral data from social media and other digital platforms. Since, reproducibility is key to the credibility and impact of scientific findings, we aim to assess current computational reproducibility practices in social science critically. We discuss the challenges and barriers hindering computational reproducibility and plan for efficient and easy-to-follow approaches toward enhancing computational reproducibility, transparency, adaptability, and citation potential.
A central focus of the workshop will be the introduction of guidelines and checklists specifically designed to support computational reproducibility in social science research. These resources are applied on a dedicated computational methods platform called Methods Hub as a structured framework for transparent, reusable, and reproducible computational methods.
Participants will engage in interactive discussions and hands-on activities to evaluate these tools, explore their applications in diverse research scenarios, and identify opportunities for improvement.
The participants’ feedback on identifying roadblocks and actionable improvements will contribute to the discussion and concluding remarks of the workshop.
Ultimately, this workshop seeks to build a dynamic interdisciplinary community that integrates perspectives from meta-science, social science, and artificial intelligence, fostering lasting collaborations and promoting the broader adoption of reproducibility standards.