Artificial Intelligence in Journalism: Impact on Text Quality
DOI:
https://doi.org/10.47475/2070-0695-2025-58-4-190-202Keywords:
artificial intelligence, media education, media literacy, media texts, neural networks, news texts, readability, editorial control, automation of journalism, Telegram channelsAbstract
The article is devoted to the study of the capabilities of artificial intelligence (AI) in editing news texts, with an emphasis on improving their purity and readability. The purpose of the work is to assess the impact of neural network technologies on the quality of media texts and determine the optimal conditions for their use in journalism. The theoretical basis of the study was modern works on the use of AI in the media industry, media literacy and digital transformation of the media, which emphasize both the potential and the risks of automating editorial processes. As part of the experiment, the authors selected five news materials from popular Telegram channels (Caution, Moscow, Topor Live, Mash, Baza, From the Spot). The texts were processed by AI, after which they were assessed according to the parameters of purity (literacy, absence of errors) and readability (ease of perception) using the Glavred.ru service. The results showed that AI effectively improves the quality of texts after editorial editing: in most cases, the purity and readability indicators increased. However, primary processing without editorial involvement sometimes resulted in decreased readability, which emphasizes the need for human control. As a result of the study, the authors conclude that artificial intelligence is an effective tool for optimizing the structure and style of texts, but its use requires mandatory editorial revision to preserve the semantic uniqueness and emotional expressiveness. Despite the ability of neural networks to process heterogeneous content, their use should be strictly dosed to avoid the loss of the author's individuality and the emergence of semantic inaccuracies. This study contributes to the scientific discussion of the transformation of media under the influence of artificial intelligence technologies, offering practical recommendations for integrating automated systems into editorial work.
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