Algorithmic screening is increasingly used in talent acquisition across large and small corporations worldwide, with an ambitious promise of eliminating idiosyncratic human biases by using identical and consistent evaluation criteria. Nonetheless, very little is known about how these algorithms are trained across a myriad of behavioral dimensions, from texts in CVs and interviews to non-verbal…

The goal of this project is to increase the performance of active learning for screening large amounts of textual data by optimizing the hyperparameters of learning algorithms in the ASReview open-source software. Users from social sciences should be able to select a set of hyperparameters optimized for textual data from their domain instead of the…

The project, situated at the department of Cultural Anthropology and the department of Methodology and Statistics, uses a combination of ethnographic and text mining methods.