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Personality in just a few words : Assessment using natural language processing

Sikström, Sverker LU orcid ; Valavičiūtė, Ieva LU and Kajonius, Petri LU (2025) In Personality and Individual Differences 238.
Abstract

Assessment of psychological constructs, such as the Big Five personality traits, has predominantly relied on standardized rating scales. While these scales have advantages, we propose that descriptive word-based responses analyzed with natural language processing (NLP) offer a promising alternative for assessing personality traits. We asked participants (N = 663) to describe either their own personality or a person high in one of the Big Five traits using five words. These responses were then analyzed using large language models, namely BERT and GPT-4, which are known for their high-performance NLP capabilities. The primary aim was to assess the validity of word-based responses analyzed by NLP in comparison to the IPIP-NEO-30 rating... (More)

Assessment of psychological constructs, such as the Big Five personality traits, has predominantly relied on standardized rating scales. While these scales have advantages, we propose that descriptive word-based responses analyzed with natural language processing (NLP) offer a promising alternative for assessing personality traits. We asked participants (N = 663) to describe either their own personality or a person high in one of the Big Five traits using five words. These responses were then analyzed using large language models, namely BERT and GPT-4, which are known for their high-performance NLP capabilities. The primary aim was to assess the validity of word-based responses analyzed by NLP in comparison to the IPIP-NEO-30 rating scale, a commonly used tool for measuring the Big Five traits. Results showed that descriptive word responses had an average prediction accuracy of up to 10 % higher than the rating scale in categorizing the Big Five traits. Additionally, semantic measures showed higher inter-rater reliability, and observer convergence was greater in assessments of others than in self-reports. These findings suggest that descriptive word-based responses may capture more observable and broad aspects of personality compared to traditional rating scales.

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author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
BERT, Big Five, GPT-4, Natural language processing, Personality
in
Personality and Individual Differences
volume
238
article number
113078
publisher
Elsevier
external identifiers
  • scopus:85216477041
ISSN
0191-8869
DOI
10.1016/j.paid.2025.113078
language
English
LU publication?
yes
id
8f2760b0-38f6-444c-a5f3-f6277c8727ea
date added to LUP
2025-03-20 14:25:37
date last changed
2025-10-14 09:33:13
@article{8f2760b0-38f6-444c-a5f3-f6277c8727ea,
  abstract     = {{<p>Assessment of psychological constructs, such as the Big Five personality traits, has predominantly relied on standardized rating scales. While these scales have advantages, we propose that descriptive word-based responses analyzed with natural language processing (NLP) offer a promising alternative for assessing personality traits. We asked participants (N = 663) to describe either their own personality or a person high in one of the Big Five traits using five words. These responses were then analyzed using large language models, namely BERT and GPT-4, which are known for their high-performance NLP capabilities. The primary aim was to assess the validity of word-based responses analyzed by NLP in comparison to the IPIP-NEO-30 rating scale, a commonly used tool for measuring the Big Five traits. Results showed that descriptive word responses had an average prediction accuracy of up to 10 % higher than the rating scale in categorizing the Big Five traits. Additionally, semantic measures showed higher inter-rater reliability, and observer convergence was greater in assessments of others than in self-reports. These findings suggest that descriptive word-based responses may capture more observable and broad aspects of personality compared to traditional rating scales.</p>}},
  author       = {{Sikström, Sverker and Valavičiūtė, Ieva and Kajonius, Petri}},
  issn         = {{0191-8869}},
  keywords     = {{BERT; Big Five; GPT-4; Natural language processing; Personality}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Personality and Individual Differences}},
  title        = {{Personality in just a few words : Assessment using natural language processing}},
  url          = {{http://dx.doi.org/10.1016/j.paid.2025.113078}},
  doi          = {{10.1016/j.paid.2025.113078}},
  volume       = {{238}},
  year         = {{2025}},
}