Causal Inference Methods in Computational Social Science

We provide a unified tutorial on causal inference methods — potential outcomes framework, structural causal models, instrumental variables, regression discontinuity, and difference-in-differences — aimed at computational social scientists transitioning from correlational to causal analysis. Each method is illustrated with a reproducible Python notebook using real-world social datasets.

Assoc. Prof. Ümit Güneş (2026). Causal Inference Methods in Computational Social Science. YTU Journal of Statistics, 1(1), 45-68. https://doi.org/10.99999/ytuj.demo.11