ABSTRACT This study employs thematic analysis and critical discourse analysis to examine the translation of news from English-language sources by BBC News Russian between January and August 2025, focusing specifically on article headlines. The aim is to uncover ideological representations in the original headlines selected for translation and to analyze ideological shifts introduced in the translated headlines. The thematic analysis identified three interrelated themes in the corpus: the Russo-Ukrainian war, international relations, and Trump. The critical discourse analysis revealed that both BBC News and BBC News Russian frame the Russo-Ukrainian war as Russian aggression against Ukraine. Headlines in both languages invoke negative evaluations of Putin, portraying him as a dictator with an aggressive foreign policy and unwillingness to end the war. They also imply a critical evaluation of Trump, highlighting his attempt to secure a ceasefire with Putin by pressuring Ukraine and framing his foreign policy as manipulative. Translated headlines introduce additional evaluations, including skepticism about U.S.–Russia ceasefire negotiations, subtle ridicule of Trump’s efforts to persuade Putin to end the war, and criticism of Trump’s broader foreign policy approach – all conveyed primarily through irony.

The translation of Romanian-language news into Hungarian is essential for supplying content to Hungarian online news portals in Romania.In the present study, we focus on news texts, as they emerge on the website of Romania’s national news agency Agerpres, and their translation into Hungarian. News texts are typically precise, accurate, and factual, which requires that their content usually employ a neutral and objective style. The question we aim to answer is whether the distortions, inaccuracies, and the other phenomena that can be spotted are translation errors or the natural ingredients of news translation that have been found in the research carried out in other countries (Bielsa–Bassnett 2009; Valdeón 2005, 2008; etc.). We do not intend to accomplish quantitative research but rather to carry out a qualitative analysis based on a case study in order to identify tendencies and observe translation practices in the field of news rendering. We intend to continue our investigation by forthcoming steps and scrutiny. The shifts, distortions, and alterations we have identified in our corpus include summarizing, reordering, adding, explicitations and suppressing information, omissions, and calque translations, all of which echo the findings of more complex research.

News outlets might see the same event from different points of view. Such different perspectives can also be observed in translated news and its sources. This study discusses the reframing in the translation of news on the Israel-Hamas war in Kompas in the Indonesian language, translated from the English news agency Associated Press (AP). This research aims to examine how reframing was applied by Kompas when translating news texts from AP. It adopts a qualitative approach and is product-oriented research as it uses translated text as the primary analysis focus and to draw conclusions. The study draws on reframing and appraisal theory. Kompas and AP were chosen as data sources for their reputable sources of news and significant impact on their respective scopes. Data analysis yielded different categories of results. The first is units of analysis (n=123), which fall into two categories: nonappraisal (n=72) and appraisal (n=51). The second is the assessment shifts of the evaluative resources that can be classified into three categories: Israel and Hamas as entities, actions taken by Israel and Hamas, and supporters of Israel and Hamas. The third is that Kompas tends to amplify assessments of Israel from negative to more negative points of view, while presenting Hamas in a more positive frame, particularly related to the translation of the group's names. The results of this study support the view that Kompas attempts to meet the Indonesian target readers' expectations and take the government’s partial stance towards Palestine.

ABSTRACT Since the University of Warwick’s news translation project in the mid-2000s, it has been a truism that journalists rarely translate whole articles but instead compose stories using texts in other languages as one source among others. However, the development of AI-based machine translation has brought about a shift in journalistic practices. Increasingly, multilingual news agencies are using these tools to produce similar stories in multiple languages. One consequence has been that researchers can now compile parallel corpora of translated stories. This article proposes a method to characterize such corpora by measuring the distance between source and target texts, a method it applies to stories published in English and French on the website SwissInfo.ch. It describes the mechanics of corpus-building, article vectorization, and the creation of a lexical substitution list that makes measurement possible. It then proposes three measures – Euclidean, Jaccard, and cosine – which have complementary strengths and weaknesses. The value of these measurement tools is heuristic: they make it possible to identify patterns that can be investigated using other methods more familiar to news translation researchers, such as interviews or direct observation.

Kashmiri language, recognized as one of the low-resource languages, has rich cultural heritage but remains underexplored in NLP due to lack of resources and datasets. The proposed research addresses this gap by creating a dataset of 15,036 news snippets for the task of Kashmiri news snippets classification, created through the translation of English news snippets into Kashmiri using the Microsoft Bing translation tool. These snippets are manually refined to ensure domain specificity, covering ten categories: Medical, Politics, Sports, Tourism, Education, Art and Craft, Environment, Entertainment, Technology, and Culture. Various machine learning, deep learning, transformer-models, and LLMs are explored for text classification. Among the models experimented for classification, fine-tuned ParsBERT-Uncased emerged as the best-performing transformer model, achieving an F1 score of 0.98. This work not only contributes a valuable dataset for Kashmiri but also identifies effective methodologies for accurate news snippet classification in the Kashmiri language. This research developed an essential dataset, which to our best belief, is the first attempt at creating a manually labelled corpus for the Kashmiri language and also devised an architecture using the best combination of embeddings, algorithms, and transformer-models for accurate text classification. It contributes significantly to the field of NLP for this underrepresented language.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-24451-4.

This study addresses the challenge of effectively integrating moral education into specialized foreign language courses. Focusing on News Translation, it develops and implements a Theme-Based and AI-Assisted pedagogical model. The core innovation lies in deliberately leveraging the inherent limitations of AI translation-such as its frequent errors in handling culture-loaded terms-as catalysts for critical thinking and value judgment. Through a structured process of AI-aided translation and guided critical post-editing, students analyze and correct AI-generated texts, engaging deeply with issues of cultural positioning and ethical responsibility in translation. Preliminary practice indicates this model successfully fosters the integration of professional skill development, critical capacity building, and values internalization. It offers a replicable, structured approach for achieving subtle yet profound moral education within foreign language and translation curricula, moving beyond superficial add-ons to deep, process-based integration. The study concludes with implications for instructional design and assessment in the age of AI.

This study explores ideological and rhetorical shifts in Arabic translations of Yemen-related political news articles published by some English-medium outlets, applying Aristotle’s model of rhetorical appeals (ethos, pathos, and logos) to uncover how translation strategies can influence the ideological framing of political discourse. The study also draws on Skopos theories of translation and rhetoric to examine how translators may intentionally manipulate credibility, emotions, and logical arguments as tools of persuading and informing to align the translated text with certain political and ideological agendas. This paper aims to investigate the extent to which translators employ rhetorical appeals to alter the message of the original text or amplify that of the translation, as well as how such modifications can contribute to the ideological positioning of the target text. The paper thus highlights the critical role of translation in shaping political narratives, offering insights into how rhetorical strategies are adapted across languages to influence public opinion. The findings reveal that translators often employ specific rhetorical techniques to align political messages with targeted ideological perspectives. It is hoped that this study can contribute to the field of translation studies by highlighting the active role of translators in shaping political discourse, suggesting that translation is not merely a linguistic exercise but a strategic act with profound ideological consequences.

Abstract This article builds on the dynamic field of research on news translation. It presents a mixed-methods analysis of a parallel corpus of news agency dispatches to further our understanding of how news is translated and the factors influencing the translation strategies which are used. It focuses on the translation of quotations in news agency dispatches that are translated from English into French. The results of quantitative and qualitative analyses of a parallel corpus of source and translated dispatches underscore the importance of quotations in news agency dispatches. However, they also show that quotations can be cut as news is translated and what determines whether quotations will be lost or retained in the translation process. The study emphasizes the need for mixed-methods approaches and calls for more comparative research on news translation.

Abstract The advancements in computing and artificial intelligence (AI) alongside the growing need for rapid and effective communication on a global scale are reshaping the landscape of translation, impacting the process, the product, and our understanding of translation. This is especially true for hybrid scenarios, which involve flexible equivalence between the source and target texts, e.g., in the translation of news, popularisation of scientific texts, transediting, and transcreation. These changes also affect existing Translation Quality Assessment (TQA) paradigms, whose scope, aims, and applications should evolve alongside these developments. This paper engages in a reflective analysis of the historical evolution, present state, and potential future professional and didactic applications of TQA. After reviewing past paradigms, the paper looks into its contemporary applications within professional and educational settings. Special attention is given to the ISO 5060:2024 and its role in shaping TQA, as well as to the integration of computer-assisted revision in translator training. The paper then discusses how current TQA approaches can be adapted to hybrid settings and how they can expand their scope and applications to interact with new technologies. This is illustrated through two applied scenarios, one regarding the summary translation of a medical academic paper for non-expert readers, and the other involving the analysis of machine translation (MT) outputs to assess their quality for post-editing purposes, improving them through AI. The paper thus exemplifies how TQA can be adapted to hybrid translation scenarios and shows how error analysis can serve not only to assess MT quality, but also to determine whether and how to improve its output through automation.

Abstract This article introduces a method to identify and classify translation equivalences in multilingual news texts and applies it to the task of creating a corpus for the study of news translation, a notably challenging area within Translation Studies. The dataset is composed of 41 Greek-English news dispatches on the topic of migration by AMNA, the Greek national news agency. Conceptually, we build on previous research on ‘comparallel’ corpus architectures, which bring together features of comparable and parallel corpora and provide the necessary flexibility to account for the non-prototypical translated data characterizing multilingual news. The automated method uses state-of-the art Natural Language Processing techniques, namely sentence and word embeddings, which make it possible to account for nuanced translation relationships, distinguishing between translated, partially translated, related, and unrelated sentence pairs. We test the method against a benchmark of manually annotated sentences from the AMNA dataset and provide examples of correctly and incorrectly classified sentence pairs. We finally build a fully-fledged comparallel corpus based on the dataset and present a case study demonstrating how the corpus can be leveraged for corpus-assisted studies of news discourse, and most notably to investigate newsworthiness and ideological shifts occurring in multilingual news.

Advancements in technology enable a swifter translation process, enhancing the circulation of information on a global scale. Nevertheless, the translation process requires supervision to maintain the quality of the news, to ensure the essence of the information is accurately conveyed in the translated output. There are various translation techniques, and typically, each agency has its own standards and regulations governing the techniques and structures. This study aims to analyze the translation techniques in translating CNN news using Molina and Albir (2004) framework and assess the translation quality using Nababan (2015) parameters. It is found that the first news translation has high accuracy but with low acceptability and readability, indicating that the translation results tend to be faithful but sacrifice the other two aspects. The second news translation tends to prioritize the presentation of readings that are easier to understand and accept by readers, but has an impact on low accuracy. The third news translation tends to be able to balance the three aspects with a difference in the average score of accuracy (2.67), which is closely aligned with the scores for acceptability and readability. Based on the final calculation with weighted scores, the results obtained show that overall, the CNN Indonesia translator succeeded in translating CNN International news well and obtained a final average score of 2.70, which is very close to the maximum score of 3.0.

Misinformation has been a global challenge for information and news exchange. Recognizing such a challenge, the UN has expressed concerns about the consequences of misinformation. Unfortunately, the problem is exacerbated when international news is subjected to deliberate modification or interference during translation culminating in reproducing fake news into the target language. The phenomenon has developed more with the spread of fake news in recent years. It is worth noting that the Arabic translation of some foreign news is significantly modified though widely spread especially in social networks. Such a situation requires serious attention to help control misleading news translation. This study addressed the spread of fake news through translation from a critical and ethical perspective. To this end, a set of original news stories and their corresponding manipulated or modified versions in Arabic were collected and examined. The modification strategies were investigated in light of Bielsa and Bassnett’s (2009) news translation strategies, followed by a critical discourse analysis using the sociocognitive approach proposed by van Dijk (2014, 2015). The results uncovered manipulation strategies such as Hyperbolization, negative other-presentation, framing, and blame transfer. The relevant ethical issues were stressed to raise awareness of translation ethics as a core principle in translation. The study outcomes are useful for researchers and the concerned public and private organizations as a first step toward developing tools to counter the proliferation of fake news through translation.

ABSTRACT This article provides an overview of the research devoted to journalistic translation in the past five years and serves as an introduction to a thematic issue comprising twelve articles on diverse topics, using various methodologies and representing the various geographical areas where news translation has received greater attention, namely Europe, North America and China. It complements the introductory article of the thematic issue of Perspectives published in 2020. The final section mentions several possible avenues of research for the future, including the study of translation in the history of news production, news translation and ideological issues, and translation and constructive news amongst others.

This study investigates translation strategies in English-Chinese financial news through a corpus-based analysis, utilizing a parallel corpus comprising over 10,000 tokens sourced from the United Nations Parallel Corpus and bilingual reports from Bloomberg and Reuters. Focusing on specialized economic terminology and culturally loaded expressions, the research categorizes translation strategies into literal translation, free translation, and cultural adaptation. Statistical results reveal that literal translation predominates (70%), particularly in technical terms such as "quantitative easing" and "monetary policy," ensuring terminological precision in financial contexts. Free translation accounts for 20%, often applied to metaphorical expressions (e.g., "bull market" translated as ""), while cultural adaptation (10%) addresses region-specific concepts like "Black Friday" localized as "." The findings highlight the tension between accuracy and readability in financial news translation, emphasizing the need for context-aware strategies to balance specialized knowledge dissemination and audience accessibility. This research contributes to translation studies by providing empirical insights into economic text localization and offers practical implications for translators and machine translation systems operating in cross-cultural financial communication.

This article explores the application of L.S. Barkhudarov's theory of equivalence in the translation of news materials about regional images. The main focus is on the selection of translation units and translation techniques to achieve maximum equivalence based on an analysis of relevant news texts. The object of the study is the translation aspects of news about Xinjiang, while the subject is texts from the Russian press, specifically materials on regional images in leading Russian media. The author analyzes in detail the choice of translation units at various levels (phonemic, morphemic, lexical, syntactic, and textual) and the application of corresponding translation strategies and methods. Special emphasis is placed on the necessity of a flexible approach to the selection of translation units in order to achieve equivalence at all linguistic levels, taking into account cultural features and context. This article conducts an analysis and generalization of the role of equivalence in the translation of news that shapes regional images, considering six linguistic levels based on this theory. Furthermore, it examines the main translation methods employed, including transcription, substitution, omission, addition, rearrangement, and adaptation, as well as their impact on the accuracy of information transfer. The main conclusion of the study is that Barkhudarov's theory of equivalence has significant theoretical value and practical applicability in translating news texts about regional images, providing a multi-dimensional referential framework for such translations. In translation practice, it is necessary to choose the level of translation justifiably and flexibly according to the text's features and dissemination goals, which allows for effective resolution of conflicts of linguistic forms at the micro level and ensures logical coherence of the text at the macro level. The novelty of the study lies in the choice of a text about regional images from news about Xinjiang as the subject of research, covering a wide range of fields, as well as the innovative comprehensive analysis of its translation within the framework of L.S. Barkhudarov's theory of equivalence, considering modern linguistic approaches.

As fake news continues to plague the exchange of international news, a growing concern is evolving about the translation quality as well. Social media users exchange international news stories that are translated and manipulated by unknown sources. Inaccurate or untrue translations of international news may reproduce fake news and mislead readers. The present study examined the translation quality of news stories that have been further manipulated when translated from English to Arabic. The dataset comprises 10 verified international news stories on various events. The translation quality was evaluated by the bilingual evaluation understudy (BLEU) metric. The findings revealed that basic information and context were targets of manipulation in the Arabic versions of foreign news. Several manipulating strategies were applied, such as adding new or irrelevant information, eliminating important details, and recontextualizing. The results are thought to shed light on the role of translation in helping identify fake news.

This study aims to provide an understanding of main theoretical concepts related to journalistic translation, how ideologies in journalistic texts are formed and the way these ideologies are reproduced in the translation process. It also raises the issue of objectivity in translating news and whether and, to what extent, it can be achieved. The goal is to offer a holistic view on the theoretical approach with which a translator needs to familiarize himself in translating news. The methodology applied is purely theoretical by investigating key-terms and theoretical models related to news translation through literature review. To this end, the article explores among others journalistic work and its characteristics, criteria for selecting news stories, news translation as a specialized type of translation and the issue of objectivity. What follows is a comprehensive analysis of the Critical Discourse Analysis (CDA) model and its practical contribution to news translation. In the concluding section, some final thoughts are expressed regarding the significance of the findings of the article. Ιt is hoped that the present analysis will make up a useful theoretical tool for professionals who wish to occupy themselves with the highly demanding specialised field of news translation.

Since the outbreak of pandemic, news has been gaining increasing interest in translation studies due to its wide reach and clear ideology implications. According to the Multi-dimensional Integration Principle of Eco-translatology, in order to ultimately accomplish the goals of “survival” and “longevity,” translators must take into account the adaptation choices of the translation within language, cultural, and communicative ecosystems in addition to being true to the original text and accommodating the reader. The translator becomes the focal point of the procedure as a result. This study examined the centrality of translators and their ideological reflections in news translation from three aspects of the integration principle using bilingual news texts from People’s Daily, China’s official media outlet, over the previous three years. This study will deepen the understanding of Translation Ecology applications, systematically grasp China’s image, stance and direction in international opinion, and enhance translators’ skills and international competence in external communications.

The paper explores the crucial role of news translation in shaping the portrayal of the Islamist discourse in news reports, specifically analyzing the practices of two leading media institutions, BBC and Al Arabiya. It emphasizes the significance of accurate and nuanced translation in avoiding misinterpretation and misrepresentation, highlighting the potential consequences of mistranslation on public opinion and policy decisions. The study delves into the textual data analysis to examine translation patterns, language directionality, and the visibility of translation, shedding light on the practices and strategies employed in news translation. By comparing the English and Arabic versions of news reports, it elucidates the impact of translation strategies on the presentation of the Islamist discourse, emphasizing the differences in contextualization, labeling, and direct quotations between the two languages. The study underscores the importance of meticulous translation practices in portraying the complexities of the Islamist discourse, aiming to bridge cultural divides and foster a more informed public discourse. It delineates the translation strategies utilized by both media institutions, such as direct quotation, deletion, and modification of language orientation, shedding light on the influence of translation beliefs on the actual translation practices adopted. The study's comprehensive analysis unveils the influence of news translation on the ideological and political standpoint of news institutions, ultimately emphasizing the pivotal role of accurate and balanced news translation in promoting a nuanced understanding of complex issues, especially in a world inundated with misinformation and propaganda. In conclusion, the study presents a thorough examination of the role of news translation in portraying the Islamist discourse in news reports, elucidating the intricate relationship between translation practices, language directionality, and the portrayal of ideological concepts. It underlines the responsibility of translators in providing accurate and nuanced translations that reflects the complexities of the Islamist discourse, ultimately contributing to a more informed and nuanced public understanding. The study's findings offer valuable insights into the translation strategies and practices employed by news institutions, highlighting the profound impact of news translation on shaping public perception and discourse.

This study explores the social and institutional practices of news translation and how the key players in newsrooms of the two media institutions, the BBC and Al Arabiya, understand and practice translation, specifically, the translation of news reports tackling Islamist discourse. It endeavors to present answers to the study questions. In this study, interviews were been conducted with the staff of BBC and Al Arabiya. The nature of the interviews that we conducted on BBC and Al Arabiya was mostly qualitative. the study approached the following resultsTranslation of the news does have a huge impact on the news that is being posted in different regions. This is why BBC and Al Arabiya have set standard operating procedures for the translation of the news. They both have their own set of guidelines and staff from both organization follows those guidelines. When it comes to Islamist discourse while translating from Arabic to English and English to Arabic both BBC and Al Arabiya are very careful in posting any of these things. They ensure that the material they post is standardized and must meet all the required guidelines to ensure impartiality so that religious sentiment should not get hurt through offending Islamic values, The news team adopts different strategies and practices as per the situation environment to make content interesting but the important thing that BBC and Al Arabiya ensure is that they are as per the guidelines set by them. This ensures the quality of the translated content. They also have language experts in their teams who have expertise in multiple languages. These language experts do not only help in the translation process but also help in language management during the translation process.