ArticleThe Journal of creative behavior2024
The Language of Creativity: Evidence from Humans and Large Language Models.
Article in The Journal of creative behavior, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Evaluation of Large Language Models as Tools, Models, and Partners in Creative Thinking Research: A Selective Narrative Review with the GCA Framework.Journal of Intelligence · 2026Review
- Large language models are homogeneously creative.PNAS nexus · 2026Article
- Establishing the behavioral feasibility of a structured story-generation paradigm for neurophysiological research.Frontiers in psychology · 2026Article
- Introducing the fusion innovation test as a new paradigm for studying realworld creative problem solving.Scientific reports · 2025Article
- Generative artificial intelligence models outperform students on divergent and convergent thinking assessments.Scientific reports · 2025Article
- Echoes in AI: Quantifying lack of plot diversity in LLM outputs.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- When ChatGPT Writes Your Research Proposal: Scientific Creativity in the Age of Generative AI.Journal of Intelligence · 2025Article
- Neural correlates of evaluative bias against artificial intelligence-labeled versus human-labeled artworks.Social cognitive and affective neuroscience · 2025Article
- Creativity and aesthetic evaluation of AI-generated artworks: bridging problems and methods from psychology to AI.Frontiers in psychology · 2025Review
- GenAI Creativity in Narrative Tasks: Exploring New Forms of Creativity.Journal of Intelligence · 2024Article
- Characterizing Features of Creative Writing in Older Adults.The journals of gerontology. Series B, Psychological sciences and social sciences · 2024Article
- Creative Evaluation: The Role of Memory in Novelty & Effectiveness Judgements.Creativity research journal · 2024Article
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Authors and funding
4 authors.
Funding
Abstract
Recent developments in computerized scoring via semantic distance have provided automated assessments of verbal creativity. Here, we extend past work, applying computational linguistic approaches to characterize salient features of creative text. We hypothesize that, in addition to semantic diversity, the degree to which a story includes perceptual details, thus transporting the reader to another time and place, would be predictive of creativity. Additionally, we explore the use of generative language models to supplement human data collection and examine the extent to which machine-generated stories can mimic human creativity. We collect 600 short stories from human participants and GPT-3, subsequently randomized and assessed on their creative quality. Results indicate that the presence of perceptual details, in conjunction with semantic diversity, is highly predictive of creativity. These results were replicated in an independent sample of stories (
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