mlsanityData to 7 Oct 2026

Large language models can replicate cross-cultural differences in personality

arXiv 2310.10679 ↗First posted 12 Oct 2023cs.CL cs.AI cs.CYcited by 8

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Abstract (arXiv)

We use a large-scale experiment (N=8000) to determine whether GPT-4 can replicate cross-cultural differences in the Big Five, measured using the Ten-Item Personality Inventory. We used the US and South Korea as the cultural pair, given that prior research suggests substantial personality differences between people from these two countries. We manipulated the target of the simulation (US vs. Korean), the language of the inventory (English vs. Korean), and the language model (GPT-4 vs. GPT-3.5). Our results show that GPT-4 replicated the cross-cultural differences for each factor. However, mean ratings had an upward bias and exhibited lower variation than in the human samples, as well as lower structural validity. We provide preliminary evidence that LLMs can aid cross-cultural researchers and practitioners.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 8 of its 47 references that are in the map. First posted on arXiv 12 Oct 2023.

Builds on

8 of 47 references.

References · 8

  1. 2017Attention Is All You Needcited by 59,932
  2. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,579
  3. 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddingscited by 1,304
  4. 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraintscited by 420
  5. 2018Women also Snowboard: Overcoming Bias in Captioning Modelscited by 236
  6. 2023Personality Traits in Large Language Modelscited by 166
  7. 2022Who is GPT-3? An Exploration of Personality, Values and Demographicscited by 112
  8. 2022Deep Lexical Hypothesis: Identifying personality structure in natural languagecited by 10

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 2; 2026: 3.

8 papers.