47 citations · 55 across the 8 of their papers we have counts for
8 papers
A Methodological Guide on Using Large Language Models for Reproducible Text Annotation in the Social Sciences and Humanities with Python and R
Qixiang Fang, Javier Garcia Bernardo, Erik-Jan van Kesteren
Large language models (LLMs) are increasingly used by researchers in the social sciences and humanities (SSH) for text analysis, particularly to automate text annotation. However,…
Tidy simulation: Designing robust, reproducible, and scalable Monte Carlo simulations
Erik-Jan van Kesteren
Monte Carlo simulation studies are at the core of the modern applied, computational, and theoretical statistical literature. Simulation is a broadly applicable research tool, used…
A density ratio framework for evaluating the utility of synthetic data
Thom Benjamin Volker, Peter-Paul de Wolf, Erik-Jan van Kesteren
Synthetic data generation is a promising technique to facilitate the use of sensitive data while mitigating the risk of privacy breaches. However, for synthetic data to be useful i…
Community detection in bipartite signed networks is highly dependent on parameter choice
Elena Candellone, Erik-Jan van Kesteren, Sofia Chelmi +1
Decision-making processes often involve voting. Human interactions with exogenous entities such as legislations or products can be effectively modeled as two-mode (bipartite) signe…
Fair inference on error-prone outcomes
Laura Boeschoten, Erik-Jan van Kesteren, Ayoub Bagheri +1
Fair inference in supervised learning is an important and active area of research, yielding a range of useful methods to assess and account for fairness criteria when predicting gr…
Privacy-Preserving Generalized Linear Models using Distributed Block Coordinate Descent
Erik-Jan van Kesteren, Chang Sun, Daniel L. Oberski +2
Combining data from varied sources has considerable potential for knowledge discovery: collaborating data parties can mine data in an expanded feature space, allowing them to explo…