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Mapping Mental Representations With Free Associations: A Tutorial Using the R Package associatoR.

Samuel Aeschbach^1,2, Rui Mata², Dirk U Wulff^1,2

¹Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany.

Journal of Cognition

|January 13, 2025

Summary

This summary is machine-generated.

Free association analysis reveals how people mentally represent complex concepts like risk and sustainability. This method, using the R package associatoR, offers insights for researchers and policymakers into societal understanding.

Keywords:

R package free association generative AI intelligence mental representations

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Area of Science:

Cognitive Psychology
Computational Social Science
Psychological Research Methods

Background:

Understanding public perception of key concepts like risk, sustainability, and intelligence is crucial for researchers and policymakers.
Current methods for assessing these perceptions are limited, leaving an underexplored avenue for deeper insights.

Purpose of the Study:

To introduce and demonstrate the utility of the R package 'associatoR' for collecting, processing, mapping, and comparing free association responses.
To provide a methodological framework for analyzing mental representations using free association data.
To explore the application of natural language processing and large language models in understanding these representations.

Main Methods:

Utilized free association tasks to gather data on mental representations.
Employed the R package 'associatoR' for data management and analysis.
Applied natural language processing techniques, including embeddings from large language models, to analyze response structures.

Main Results:

Demonstrated the capability of 'associatoR' to effectively collect and analyze free association data.
Showcased how free association analysis can uncover the structure of mental representations across different groups.
Highlighted the potential of this approach in understanding how both humans and machines conceptualize complex issues.

Conclusions:

Free association analysis is a powerful and underexplored method for mapping mental representations.
'associatoR' provides a robust tool for researchers to implement this methodology.
This approach offers valuable insights into public understanding of critical social and technological topics.