2024/03/22 by Samuel Aeschbach, Rui Mata, Dirk U. Wulff · 1 voice
Computer Science · #Data Analysis with R
paper · pdf · doi:10.31234/osf.io/ra87s
openalex publication_date 2024/03/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
People’s understanding of topics and concepts such as risk, sustainability, and intelligence can be important for psychological researchers and policymakers alike. One underexplored way of accessing this information is to use free associations to map people’s mental representations. In this tutorial, we describe how free association responses can be collected, processed, mapped, and compared across groups using the R package associatoR. We discuss study design choices and different approaches to uncovering the structure of mental representations using natural language processing, including the use of embeddings from large language models. We suggest that free association analysis presents a powerful approach to revealing how people and machines represent key social and technological issues.