By Catherine Chen and Carsten Eickhoff
This code corresponds to the paper: Evaluating Search System Explainability with Psychometrics and Crowdsourcing, in Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’24), July 14–18, 2024, Washington, DC, USA.
If you find this code or any of the ideas in the paper useful, please consider citing:
The code in this repo utilizes factor_analyzer and semopy Python packages to conduct Structural Equation Modeling. For result reproducibility, we provide the data collected via crowdsourcing on Amazon Mechanical Turk and Prolific. The dataset has been anonymized and any unique identifiers have been removed.
Corresponding author: Catherine Chen