Aeschbach Samuel, Mata Rui, Wulff Dirk U
Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany.
Center for Cognitive and Decision Sciences, University of Basel, Basel, Switzerland.
J Cogn. 2025 Jan 6;8(1):3. doi: 10.5334/joc.407. eCollection 2025.
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 . 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 posit that free association analysis presents a powerful approach to revealing how people and machines represent key social and technological issues.
人们对风险、可持续性和智能等主题和概念的理解,对心理学研究者和政策制定者而言都可能至关重要。一种尚未得到充分探索的获取此类信息的方法是利用自由联想来描绘人们的心理表征。在本教程中,我们描述了如何使用R包来收集、处理、描绘自由联想反应,并在不同群体间进行比较。我们讨论了研究设计选择以及使用自然语言处理来揭示心理表征结构的不同方法,包括使用来自大语言模型的嵌入。我们认为自由联想分析是一种揭示人和机器如何表征关键社会和技术问题的有力方法。