Comparative Analysis of Linguistic and Stylistic Characteristics of Human and Artificially Generated Media Texts

Abstract

The rapid rise of generative artificial intelligence (AI) has created a new linguistic challenge: distinguishing human from machine-produced media texts. Understanding the cognitive, stylistic, and pragmatic characteristics of AI-generated content is crucial for evaluating its impact on communication quality and reliability. This study aims to identify and characterize linguistic and stylistic features of AI-generated media texts compared to authentic journalistic publications. Corpus, stylometric, cognitive-pragmatic, and discursive analyses were employed to assess lexical, syntactic, semantic, and rhetorical dimensions. Results indicate that texts produced by models such as ChatGPT, Gemini, and BingAI exhibit higher grammatical accuracy, standardized syntax, reduced metaphoricity, and lower emotional expressiveness than human texts. Five parameters—grammatical variability, semantic richness, pragmatic relevance, rhetorical organization, and stylistic expression—determine the “humanness” of a text. A classification of stylistic models and linguistic markers was developed to identify text origin and evaluate its cognitive and communicative depth. The findings have practical applications for automated detection of AI authorship, enhancing digital media literacy, and establishing ethical standards for AI use in journalism and communication.

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