Synthetic Survey Data Generation and Evaluation
Published in Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’25), 2025
An end-to-end evaluation of five synthetic data generation methods for survey microdata using utility, fidelity, and privacy metrics.
Recommended citation: Yanru Jiang, Siyu Liang, and Junwon Choi. 2025. Synthetic Survey Data Generation and Evaluation. In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1 (KDD ’25). Association for Computing Machinery, New York, NY, USA, 2292–2302. https://doi.org/10.1145/3690624.3709421
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