Don’t pull any old personality taxonomy from the shelf: The performance of historical and sample derived taxonomies in extracting personality information from text

Substantial efforts have been made to develop comprehensive taxonomies of personality traits in many languages. Nevertheless, given that what is important and salient in individuals’ lived experience might be changing over time, this raises the question about the long-term usefulness of ‘off-the-shelf’ taxonomies developed decades ago. In the current study we used a bottom-up approach to create a large sample-specific taxonomy of personality terms. We subsequently examined the overlap and sensitivity of this taxonomy compared to an established trait taxonomy in the same language. Overall, we found that the two taxonomies only showed limited overlap with a pronounced divergence in emotionality (Neuroticism) and social aspects (Agreeableness) of personality. In addition to this, we found that while the personality assessment extracted from self-descriptions using the established taxonomy showed alignment with participants’ self-rated personality, especially Extraversion, Agreeableness, and Neuroticism, the sample-specific taxonomy showed a significantly greater alignment between text-based and self-rated personality. In summary, our current study highlights the need to extend our thinking about the psycholexical hypothesis, moving away from assumptions of time invariant language encoding to more explicitly recognizing temporal and sample-specific dynamics underpinning the expression and use of personality trait terms.

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Publication Details

Journal
Measurement Instruments for the Social Sciences
Published
2026-04-16
DOI
https://doi.org/10.5964/miss.16869
Primary Topic
Personality Traits and Psychology
Type
article
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article

Don’t pull any old personality taxonomy from the shelf: The performance of historical and sample derived taxonomies in extracting personality information from text

Ronald D. Fischer, Johannes A. Karl
Measurement Instruments for the Social Sciences
Personality Traits and Psychology
article

Don’t pull any old personality taxonomy from the shelf: The performance of historical and sample derived taxonomies in extracting personality information from text

Ronald D. Fischer, Johannes A. Karl
article en

Abstract

Substantial efforts have been made to develop comprehensive taxonomies of personality traits in many languages. Nevertheless, given that what is important and salient in individuals’ lived experience might be changing over time, this raises the question about the long-term usefulness of ‘off-the-shelf’ taxonomies developed decades ago. In the current study we used a bottom-up approach to create a large sample-specific taxonomy of personality terms. We subsequently examined the overlap and sensitivity of this taxonomy compared to an established trait taxonomy in the same language. Overall, we found that the two taxonomies only showed limited overlap with a pronounced divergence in emotionality (Neuroticism) and social aspects (Agreeableness) of personality. In addition to this, we found that while the personality assessment extracted from self-descriptions using the established taxonomy showed alignment with participants’ self-rated personality, especially Extraversion, Agreeableness, and Neuroticism, the sample-specific taxonomy showed a significantly greater alignment between text-based and self-rated personality. In summary, our current study highlights the need to extend our thinking about the psycholexical hypothesis, moving away from assumptions of time invariant language encoding to more explicitly recognizing temporal and sample-specific dynamics underpinning the expression and use of personality trait terms.

Measurement Instruments for the Social SciencesVol. 8
Victoria University of Wellington (NZ), D’Or Institute for Research and Education (BR)
Openalex Percentile: Top 13%
Personality Traits and Psychology
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Don’t pull any old personality taxonomy from the shelf: The performance of historical and sample derived taxonomies in extracting personality information from text — Ronald D. Fischer, Johannes A. Karl · Measurement Instruments for the Social Sciences (2026) | TGRS Research Map | TGRS