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All Journal Journal Albion : Journal of English Literature, Language, and Culture
Roselynn, Vivian Angela
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Arts Humanities Languange, Linguistic, Communication & Media Social Sciences

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Comparative study of news headlines using Bing translator and DeepL Roselynn, Vivian Angela; Bowo, Tri Arie; Sigalingging, Bob Morison
Journal Albion : Journal of English Literature, Language, and Culture Vol 7, No 1 (2025): Issue 1
Publisher : Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/albion.v7i1.11571

Abstract

This research examines the application of Nida’s (1964) formal equivalence theory in machine translation, with a focus on the structural and grammatical aspects of CNN headlines translated by Bing Translator and DeepL. This research uses a descriptive qualitative approach, analyzing translated headlines related to the 2024 United States Election. Data was collected from CNN’s official website from October to November 2024, and translations were obtained from both machine translation tools. The analysis shows that whereas both translation tools attempt to maintain structural accuracy, Bing Translator tends to preserve rigid sentence structures, while DeepL adapts phrases to improve fluency, sometimes at the expense of grammatical accuracy. A readability assessment, based on the researcher’s interpretation, shows that DeepL produces smoother translations, which are more accessible to readers. This research contributes to the machine translation reliability discussion in journalism and emphasizes the challenge of maintaining formal equivalence while ensuring readability. Future research can explore a broader corpus or integrate computational linguistic analysis to improve translation evaluation methodology.Keywords:  Formal Equivalence; Machine Translation; News Translation; Readability;  News Headlines
Co-Authors Sigalingging, Bob Morison Tri Arie Bowo