Comparative analysis of textual complexity in human and machine translation: A case study of an advertising text translated by Mexican professionals and ChatGPT-4

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Published: May 27, 2026
DOI: https://doi.org/10.6035/MonTI.2026.18.03
Keywords:
machine translation, artificial intelligence, advertising texts, text complexity, ChatGPT-4

Main Article Content

Angelvs Gutiérrez
Universidad Nacional Autónoma de México
Ioana Cornea
Universidad Nacional Autónoma de México

Abstract

This study compares the text characteristics of the translations of an advertising text produced by two groups of professional Mexican translators —one with formal training and one without it— and the one translated by ChatGPT-4. The analysis focused on six linguistic parameters: lexical density per clause, overall lexical density, lexical diversity, grammatical intricacy, average sentence length, and total translation length. The results show that ChatGPT-4 achieved higher values than both translator groups across all parameters. Its translation exhibited complex structures like those produced by trained translators, and high lexical density similar to that of the untrained group. The study concludes that further research involving other text types is necessary to identify their specific textual features and to reaffirm the importance of human participation in translation processes mediated by artificial intelligence.

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How to Cite
Gutiérrez, A., & Cornea, I. (2026). Comparative analysis of textual complexity in human and machine translation: A case study of an advertising text translated by Mexican professionals and ChatGPT-4. MonTi Monografías De Traducción E Interpretación, (18). https://doi.org/10.6035/MonTI.2026.18.03
Issue
No. 18 (2026): Artificial intelligence at the service of translation: research on new technological achievements
Section
Articles
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Author Biographies

Angelvs Gutiérrez, Universidad Nacional Autónoma de México

Angelvs Gutiérrez Carrillo is a translator and a doctoral student in Linguistics at the National Autonomous University of Mexico, where she also completed a Master’s degree in Applied Linguistics. Her current research focuses on the evaluation of post-editing processes across different text types, with particular emphasis on translation assessment and the use of artificial intelligence in computer-assisted translation tools. Her academic interests also include systemic functional linguistics and computational linguistics, fields through which she seeks to integrate theoretical approaches and technological tools for text analysis.

Ioana Cornea, Universidad Nacional Autónoma de México

Ioana Cornea holds a Ph.D. in Specialized Translation Studies from Pompeu Fabra University, Barcelona. She is currently a tenured professor at the National School of Languages, Linguistics, and Translation (ENALLT) at the National Autonomous University of Mexico (UNAM), where she teaches courses in specialized translation, terminology, and translation theories in both the Bachelor's in Translation and the Master's in Applied Linguistics programs. She also collaborates with the Master’s Program in Translation and Interpretation of Indigenous Languages at the Benito Juárez Autonomous University of Oaxaca, where she teaches interpretation into Mexico’s Indigenous languages.

She leads several research projects on legal translation studies and terminology for translation. She has taught numerous workshops and teacher training courses on specialized translation and tradumatics, the didactics of legal translation, terminology, and terminotics. She has participated in many national and international conferences and is the founder of the ENALLTerm translation studies database.

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