3 papers
stat.OT2026
Making Uncertainty Visible: Multiverse Analysis for Robust Computational Social Science
Maximilian Linde, Jun Sun, Paul Balluff +2
Through case studies, we demonstrate how multiverse analysis can strengthen the robustness and transparency of computational social science findings against alternative methodologi…
cs.LG2023
Misclassification in Automated Content Analysis Causes Bias in Regression. Can We Fix It? Yes We Can!
Nathan TeBlunthuis, Valerie Hase, Chung-Hong Chan
Automated classifiers (ACs), often built via supervised machine learning (SML), can categorize large, statistically powerful samples of data ranging from text to images and video,…
cs.CY2023
Computational Reproducibility in Computational Social Science
David Schoch, Chung-hong Chan, Claudia Wagner +1
Replication crises have shaken the scientific landscape during the last decade. As potential solutions, open science practices were heavily discussed and have been implemented with…