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The language of AI and human poetry: a comparative lexicometric study

This study conducts a lexicometric analysis to compare the lexical richness and diversity in poetry generated by AI models with that of human poets. Employing a robust dataset that includes 1,333 AI-generated poems and 517 humanauthored poems across seven distinct poetic eras, six key lexical metric...

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Main Author: Afendi Hamat,
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2024
Online Access:http://journalarticle.ukm.my/24405/1/TE%201.pdf
http://journalarticle.ukm.my/24405/
https://ejournal.ukm.my/3l/issue/view/1720
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spelling my-ukm.journal.244052024-10-21T07:41:12Z http://journalarticle.ukm.my/24405/ The language of AI and human poetry: a comparative lexicometric study Afendi Hamat, This study conducts a lexicometric analysis to compare the lexical richness and diversity in poetry generated by AI models with that of human poets. Employing a robust dataset that includes 1,333 AI-generated poems and 517 humanauthored poems across seven distinct poetic eras, six key lexical metrics—Maas Index, MTLD, MATTR, HD-D, Hapax Legomenon Ratio, and Lexical Density—were applied for comparative analysis. The lexical characteristics of the poems were studied through a series of statistical tests and machine learning techniques, including Mann-Whitney U tests, Cliff's Delta, and Random Forest classification. The findings reveal a marked lexical superiority in human poetry, evidenced by significant differences and large effect sizes in all metrics except Lexical Density. HD-D emerged as the most discriminating factor, adeptly differentiating human poetry from its AI-generated counterpart. Further analysis identified the GPT-4 model as exhibiting the closest alignment to human poetry in terms of lexical attributes. The study discusses these outcomes in the context of AI's evolving linguistic competencies, shedding light on the inherent challenges and future prospects of AI in creative writing. Thus, this research provides an empirical framework for assessing AI’s language generation abilities and sets the stage for further interdisciplinary exploration into the frontiers of artificial creativity. Penerbit Universiti Kebangsaan Malaysia 2024-06 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/24405/1/TE%201.pdf Afendi Hamat, (2024) The language of AI and human poetry: a comparative lexicometric study. 3L; Language,Linguistics and Literature,The Southeast Asian Journal of English Language Studies., 30 (2). pp. 1-20. ISSN 0128-5157 https://ejournal.ukm.my/3l/issue/view/1720
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description This study conducts a lexicometric analysis to compare the lexical richness and diversity in poetry generated by AI models with that of human poets. Employing a robust dataset that includes 1,333 AI-generated poems and 517 humanauthored poems across seven distinct poetic eras, six key lexical metrics—Maas Index, MTLD, MATTR, HD-D, Hapax Legomenon Ratio, and Lexical Density—were applied for comparative analysis. The lexical characteristics of the poems were studied through a series of statistical tests and machine learning techniques, including Mann-Whitney U tests, Cliff's Delta, and Random Forest classification. The findings reveal a marked lexical superiority in human poetry, evidenced by significant differences and large effect sizes in all metrics except Lexical Density. HD-D emerged as the most discriminating factor, adeptly differentiating human poetry from its AI-generated counterpart. Further analysis identified the GPT-4 model as exhibiting the closest alignment to human poetry in terms of lexical attributes. The study discusses these outcomes in the context of AI's evolving linguistic competencies, shedding light on the inherent challenges and future prospects of AI in creative writing. Thus, this research provides an empirical framework for assessing AI’s language generation abilities and sets the stage for further interdisciplinary exploration into the frontiers of artificial creativity.
format Article
author Afendi Hamat,
spellingShingle Afendi Hamat,
The language of AI and human poetry: a comparative lexicometric study
author_facet Afendi Hamat,
author_sort Afendi Hamat,
title The language of AI and human poetry: a comparative lexicometric study
title_short The language of AI and human poetry: a comparative lexicometric study
title_full The language of AI and human poetry: a comparative lexicometric study
title_fullStr The language of AI and human poetry: a comparative lexicometric study
title_full_unstemmed The language of AI and human poetry: a comparative lexicometric study
title_sort language of ai and human poetry: a comparative lexicometric study
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2024
url http://journalarticle.ukm.my/24405/1/TE%201.pdf
http://journalarticle.ukm.my/24405/
https://ejournal.ukm.my/3l/issue/view/1720
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score 13.211869

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