The present contribution offers a map of social psychology through the analysis of scientific publications in the field’s pivotal North American journal, the Journal of Personality and Social Psychology. The titles of a comprehensive set of papers published in the journal (1965–2021) were collected, yielding a total of 10,222 items. The corpus thus constructed underwent several stages of preprocessing until the final conversion into a terms x time-points matrix, where terms are stemmed words and multi-words. After normalizing frequencies via a chi square-like transformation, clusters of words portraying similar temporal patterns were identified by functional (textual) data analysis and distance-based curve clustering. Among the best candidates in terms of the number of clusters, the solution with six clusters has been chosen and described, as it summarizes the evolution of the social psychology keywords (i.e., their life cycle) in an effective and interpretable manner. It reveals increasing, decreasing, and stable word trends, highlighting methods, theories, and topics that have become more popular in recent years, have lost popularity, or have remained in common use. Moreover, different trends with peaks in specific years highlight the most successful moments of theories and topics. The results point out the contribution that quantitative analysis of textual data can make to the study of a discipline’s history.

Life cycle of ideas in the Journal of Personality and Social Psychology: A history of US social psychology

Valentina Rizzoli;Arjuna Tuzzi
2022

Abstract

The present contribution offers a map of social psychology through the analysis of scientific publications in the field’s pivotal North American journal, the Journal of Personality and Social Psychology. The titles of a comprehensive set of papers published in the journal (1965–2021) were collected, yielding a total of 10,222 items. The corpus thus constructed underwent several stages of preprocessing until the final conversion into a terms x time-points matrix, where terms are stemmed words and multi-words. After normalizing frequencies via a chi square-like transformation, clusters of words portraying similar temporal patterns were identified by functional (textual) data analysis and distance-based curve clustering. Among the best candidates in terms of the number of clusters, the solution with six clusters has been chosen and described, as it summarizes the evolution of the social psychology keywords (i.e., their life cycle) in an effective and interpretable manner. It reveals increasing, decreasing, and stable word trends, highlighting methods, theories, and topics that have become more popular in recent years, have lost popularity, or have remained in common use. Moreover, different trends with peaks in specific years highlight the most successful moments of theories and topics. The results point out the contribution that quantitative analysis of textual data can make to the study of a discipline’s history.
2022
Proceedings of the 16th International Conference on Statistical Analysis of Textual Data
979-12-80153-31-9
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3456036
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