English News Research Articles

A Study on the Evidential Markers in English News Discourse from the Perspective of Engagement—A Case Study of China Daily

A Study on the Evidential Markers in English News Discourse from the Perspective of Engagement—A Case Study of China Daily

Landscape of Large Language Models in Global English News: Topics, Sentiments, and Spatiotemporal Analysis

Landscape of Large Language Models in Global English News: Topics, Sentiments, and Spatiotemporal Analysis

An Ensemble Keyword Extraction Model for News Texts with Statistical and Graphical Features

Keyword extraction is an essential tool for many text mining applications such as automatic indexing, summarizing, classification, clustering and automatic filtering. Automated keyword extraction is essential as the daily text data to be reached and processed have increased tremendously over the Internet, e.g. millions of news articles are published daily online. In this paper, a novel ensemble model for automatic extraction of keywords from news articles is proposed. The proposed model handles keyword extraction as a sequence labeling task. Two sub-modules representing the statistical and graphical features by their calculated scores for each input token were combined in the token classification module. The Ensemble Token Classification module was trained and tested separately with the ensemble algorithms Random Forest, XgBoost, Decision Tree and Voting Classification. For training, we collected two news datasets from Kazakh and Russian news sites published in Cyrillic alphabet. We also collected an Arabic news dataset, ArabianNews. The performance of the model was also compared with the widely used 500N-KPCrowd dataset in the literature, which consists of English news content in Latin alphabet. The proposed model achieved the best performance with an [Formula: see text]-score of 0.71 and 0.86 on the 500N-KPCrowd and Russian datasets, respectively. We attained the best [Formula: see text]-score (0.97) with the KazakhNews and ArabianNews datasets.

Winning hearts in Southeast Asia? News sentiment on China amidst the US–PRC trade war

How did the trade rivalry between the United States and China impact China's foreign public image in the ASEAN press? In the context of Southeast Asia's mixed attitude toward China, this article argues that the trade war between China and the United States heightened negative sentiment on China, especially in states grappling with the latter as a security threat, but whose investment climate has been slower to respond to the restructuring of the global supply chain. Drawing from econometric analyses of news sentiment mined from a corpus of 75,619 online English news articles in all 10 Southeast Asian countries from January 2016 to March 2020, we find that the trade war induced negative news sentiment on China in the ASEAN press. However, foreign visits to and from China appear to have been favorably regarded and helped boost China's image in the region. The findings remind that there may be a need for China to rethink its carrot-and-stick strategy to win the hearts and minds of its ASEAN neighbors.

Discrepancies in the portrayal of Japan’s nuclear water release in Chinese and US media outlets: A corpus-based news values analysis of marine disputes

This article aims to explore the reactions and cognitions of Chinese and US societies toward Japan’s nuclear water release by comparing the methods used to construct this event in media reports from these two countries. Adopting corpus linguistic methods and a discursive news value analysis approach, this study examines news values through key words, nomination strategies and photographs in Chinese and US mainstream English language news coverage. The results show that by exercising overall control in multimodal news devices, the Chinese media dominantly constructed Japan’s nuclear water release as an environmentally harmful and legally irresponsible behavior for international society and demonstrated a prominent antagonistic position and critical attitude, while the US media mainly constructed Japan’s nuclear water release as a technically safe and politically rational behavior and manifested its neutral position and acceptive attitude. The results indicate that the acceptance of US society was supported by Japan’s technical treatment of nuclear waste water and by Japan’s political authorities’ justification for their behaviors, while the opposition of Chinese society was supported by their inquiries about the illegality of Japan’s behavior and their worries about the damage caused by Japan to the ocean environment and to the security of the international community. This study revealed the social cognitive grounds for supporting the political positions of the two countries in terms of Japan’s nuclear water release and demonstrated an effective sociological analysis method for examining the maritime disputes and marine strategies of different countries.

Exploring Risk Factors of Suicidal Behaviour among Medical Professionals in the UK: A Retrospective Analysis of Online News Portals

Suicide is a significant global health burden. The demanding nature of the healthcare profession, combined with unique stressors and challengses, puts medical professionals at risk of mental health difficulties, including suicidal ideation and attempts. This study aims to investigate suicidal behaviour among medical professionals in the United Kingdom by reviewing online news portals and focusing on the risk factors associated with suicide. Seven online news portals from the UK were purposefully selected for the study, focusing on news reports of suicides among medical professionals. Only English online news portals were chosen, as English is the standard language in the country. Out of the 61 reports, 37.7% of the reported suicides were among males, and 62.3% were among females. The age distribution of the suicide reports revealed that the majority of the cases are within the 20-30 age range (42.6%). Mental health issues and fear of losing their job were also prominent reasons (24.6%). Suicide among healthcare professionals in the United Kingdom has drawn little attention. Suicide is more prevalent in early adulthood and among female professionals. Nurses, doctors, and junior doctors are more likely to commit suicide.

Discrepancies in the newsworthiness of maritime security in Chinese and US media outlets: a corpus-based discursive news values analysis

This article analyzes and compares the news values constructed in the English news reporting from Chinese and US mainstream media around events concerning maritime security, revealing how the related events have been packaged and sold differently in the two societies, uncovering the discrepancies in Chinese and US social visions on maritime security, and exploring the social attitudes underpinning the constant conflicts between the two countries in the marine sphere. Adopting corpus linguistic methods and the discursive news values analysis (DNVA) framework, this study examines news values through keywords, naming strategies, and images contained in Chinese and US mainstream English news outlets. The results show that Chinese media established the news values of Positivity and Proximity prominently through both textual and visual reporting, by emphasizing common international interests, advocating diplomatic joint cooperation and demonstrating optimistic attitudes towards the future of marine environment. By contrast, US media keenly construed Negativity and Eliteness, by highlighting the exclusive national interests/security of the US, dwelling on threats from other countries and distinctly demonstrating worries, fears, anger and violence. The differences in newsworthiness reflect that maritime security has been constructed in discrepant ways in Chinese and US society: as international joint security with optimistic perspective in China, and as exclusive national security with pessimistic perspective in US. This study has improved and supplemented the results of the previous China-US marine policy studies by the findings of the social emotions/cognition towards maritime policy revealed through newsworthiness analysis.

Application of ELAN in Human-Machine Mutual Translation of English for the News

The translation of English news means the process of converting news articles published in English into another language. These articles may also be referred to as English news. This process comprises understanding the substance of the source article and accurately translating its tone and intent into the target language. A human translator or machine translation software can be used to perform the translation manually. In the disciplines of software globalization and technological translation, the Human-Machine Mutual Translation technique has grown significantly with the advancement of civilization and the quickening growth of research and innovation. Because of this practical need, translators have begun to focus more on machine translation and have conducted some productive research in this area. As a result, we suggested the EUDICO Linguistic Annotator (ELAN) in Human-Machine mutual translation of English for the news. EUDICO stands for European Distributed Corpora Project. The Max Planck Institute for Psycholinguistics created the EUDICO Linguistic Annotator as a software program for the linguistic annotation of language data. For this study, the English news dataset was used. The data were pre-processed by using normalization. The results were evaluated using performance metrics such as translation quality, precision, BLEU, recall, and computation time. The findings show that the recommended procedure provides an accurate translation of English news when compared to previously used methods. The results demonstrated that translation quality and computation time of proposed model are 95% and 60s respectively.

Intersectional race-gender stereotypes in natural language.

How are Asian and Black men and women stereotyped? Research from the gendered race and stereotype content perspectives has produced mixed empirical findings. Using BERT models pre-trained on English language books, news articles, Wikipedia, Reddit and Twitter, with a new method for measuring propositions in natural language (the Fill-Mask Association Test, FMAT), we explored the gender (masculinity-femininity), physical strength, warmth and competence contents of stereotypes about Asian and Black men and women. We find that Asian men (but not women) are stereotyped as less masculine and less moral/trustworthy than Black men. Compared to Black men and Black women, respectively, both Asian men and Asian women are stereotyped as less muscular/athletic and less assertive/dominant, but more sociable/friendly and more capable/intelligent. These findings suggest that Asian and Black stereotypes in natural language have multifaceted contents and gender nuances, requiring a balanced view integrating the gender schema theory and the stereotype content model. Exploring their semantic representations as propositions in large language models, this research reveals how intersectional race-gender stereotypes are naturally expressed in real life.

Development of a Smartphone Application and Chrome Extension to Detect Fake News in English and European Portuguese

Development of a Smartphone Application and Chrome Extension to Detect Fake News in English and European Portuguese

Presupposition in English news headlines: A Pragma-linguistic Study

Presupposition in English news headlines: A Pragma-linguistic Study

Exploring Pragmatic Adaptation in Television News Translation: A Case Study of Moroccan National TV

The study explores pragmatic adaptation in translating foreign TV news, focusing on Moroccan National TV practices. Translation connects cultures, necessitating an understanding of pragmatics for effective communication. Investigating this complex process is crucial to ensure that translated discourse resonates with the target audience. Foreign news, following Baker's multifunctional approach, seeks to influence audiences, demanding meticulous adaptation of linguistic nuances by translators. The study examines three axes: TV news linguistic style, translation techniques, and their efficacy. Data from translated foreign news aired on Moroccan National TV in Arabic will be analyzed, focusing on language style and register. Pragmatic adaptations in TV news translation will be scrutinized, evaluating effectiveness in fidelity to the source. A qualitative approach will be used, aligning with the study's focus on pragmatic adaptation techniques. Primary sources include culturally rich English news broadcasts translated into Arabic by Moroccan National TV translators, supplemented by al-Oula TV news topics. Through this investigation, the study aims to deepen understanding of translating foreign TV news dynamics and illuminate pragmatic adaptations in the Moroccan context.

Investigating Saudi EFL Female University Students’ Command of Journalistic Writing: An SFL-based Study on Textual Organization

This study examines written literacy outcomes among Saudi female university students undertaking an EFL journalistic course over fourteen weeks. It specifically aims to explore their competence in the English hard news genre. It, thus, seeks to address the following question: after completing the course, to what degree did students create texts structurally matching the conventional English news report? The significance of this study lies in its integration of media and education, employment of linguistic analysis based on Systemic Functional Linguistics, and use of English expert news reports for comparison with students’ journalistic texts. It deployed the genre-based pedagogy devised within the Sydney School to design the news writing course. Twenty-five students undertook such a course during the 2022 academic year. This study gathered those students’ writing to subject it to linguistic scrutiny, assessing each student over one news report after completing the course. It reports that, after the course, half of the class developed their ability to produce the genre of the standard English language hard news report. Those students created texts that matched the professional news articles in the corpus, thus effectively following the textual features of such a genre.

How can we detect news surrounding community safety crisis incidents in the internet? Experiments using attention-based Bi-LSTM models

Reports related to community safety crisis incidents are being escalated and shared on social media and other online digital platforms. These reports must be addressed quickly to concerned organizations to provide welfare support to individuals and communities in crisis, to protect their lives, and to obtain justice. To achieve this, we proposed a framework termed detection of Community Safety Crisis Incidents (CSCI) reports using an attention-based Bidirectional Long Short-term Memory (att-Bi-LSTM). Amharic reports in Ethiopia were selected as the object of study for the implementation of the detection model due to the high CSCI report rate in the region. We gathered the textual data and spoken speech content reports from famous worldwide media websites, Twitter, and YouTube platforms utilizing data crawling techniques. The proposed model achieved 90.93 % accuracy for the text test dataset and 82.10 % accuracy for the voice test dataset on the text-based pre-training model. The model was also tested on English news, yielding an accuracy of 85.92 %.

Are Transboundary Water Events Reported Differently in French and English News for Conflict and Cooperation Dynamics?

Media coverage of water events in transboundary river basins reflects the views of both riparian countries and beyond, and the conflict and cooperation dynamics could be biased due to the linguistic diversity. The aim of this study is to investigate whether any deviation exists in the depiction of water conflict and cooperation dynamics as reflected in the sentiments of French and English news articles, taking the Lancang–Mekong River basin and the Nile River basin as case studies. The results showed that news articles in English itself can reflect the trends of the cooperative or conflictive sentiments of the water events occurring within the basin, but French news is complementary in examining the attitudes and values of a few countries towards the shared river. The study would serve as an important reference for the perspective analysis of all riparian countries, as well as a basis for comprehending water conflict/cooperation dynamics in multiple languages.

A Comparative Analysis of Attitude Resources in Chinese and American English News Reports on “Roe v. Wade”

In 1973, "Roe v. Wade" (hereinafter referred to as Roe) became one of the important judgements in modern American society because of its establishment of women's reproductive choice. In 2022, the US Supreme Court officially overturned the Roe case, which also caused an uproar at home and abroad. News media, as an important information dissemination medium, widely influences readers' attitudes and opinions. This paper mainly conducted by the application of the Appraisal Theory, which has developed by the linguist J. R. Martin covering three subsystems: attitude, engagement and graduation, to the study of news reports concerning the Roe. The study is focus on the perspective of the attitude system, and the research corpus consists of a total of 10 news articles selected from two mainstream media both in China and the U.S., China Daily and New York Times. Using a combination of quantitative and qualitative methods, this study has discussed in detail the attitude resources in the overturning of Roe in Chinese and American news discourse. Through analysis and comparison, the author finds that there are similarities and differences in the overall distribution of attitude resources between the two media. First of all, the distribution of attitude resources between the two sides is roughly in the same trend. Secondly, New York Times employs more attitude resources than that of China Daily, with a dominant air of negative attitude resources.

Investigating Appraisal and the Language of Evaluation in Fake News Corpora

AbstractThe present corpus study, which is grounded in Appraisal Theory, investigates evaluative language use in fake news in English. The primary aim is to find out how and why, if at all, evaluative meanings are construed differently in fake news compared to genuine news. The secondary aim is to explore potential differences between types of fake news based on contextual factors. The data are from two carefully-designed corpora containing both fake and genuine news: a single-authored corpus and a multi-authored corpus. Both corpora contain false information that is meant to deceive, but they also differ from each other in terms of register, genre and the motivational goals of the authors. Through qualitative and quantitative analyses, we show that there are systematic differences in the occurrence of Appraisal expressions across fake and genuine news, with Appraisal being more common in the former. However, the exact nature of the affective, dialogic and modal expression of fake news is influenced by contextual factors that, so far, have largely been ignored in fake news research. Therefore, the study has important implications for the development of fake news detection systems based on data sources of different kinds, a task which is in grave need of the input of corpus linguists.

Genre-structural analysis of Arabic accident news reporting

Abstract This paper is concerned with an exploration of the structural arrangement of Arabic hard news reporting with reference to a corpus of twenty accident news stories drawn from two leading Middle Eastern news organizations, Aljazeera and Alarabiya. A range of journalistic traditions has been examined with respect to organizational structures used in their hard news reporting texts. Within journalism discourse analysis, the nucleus-satellite structure developed by scholars of Systemic Functional Linguistics (SFL) is commonly found in news reporting in English and across various languages. However, news media texts in some cultures, such as Arabic, have not undergone any close scrutiny from a generic perspective. Accordingly, this study attempts to fill such a gap by investigating the genre-related features of the Arabic accident reports, drawing on the insights provided by SFL literature on the news story as a genre. It employs various lines of analysis such as textual deconstruction, timeline, radical editability, and lexical chaining. The findings of these analyses suggest that the Arabic accident news reports are non-chronologically organized operating with the lead-dominated orbital model, and thus generically bearing a close resemblance to the English news reports.

Spanish Vs. English Language Media Consumption and Latino Political Trust and Efficacy

ABSTRACT Do Latinos who consume more Spanish language media relative to English language media express greater political trust and efficacy? While research produces increasing evidence that variations in English language media content shape core democratic attitudes like political trust, and that Spanish language media shapes acculturation and issue attitudes among Latinos, research has not explored whether broader linguistic media environments shape attitudes fundamental to democracy. Given revolutionary changes the English language media environment, and stark contrasts between English and Spanish language media environments in terms of fragmentation, ideological and partisan news reporting, narratives portraying Latinos as a “threat,” and Latino-oriented and affirming content, relative consumption of Spanish or English language news may come with important implications. Bilingual Latinos who consume varying mixtures of media from these environments offer a unique population for exploring these relationships. Building off studies relating patterns of Latino acculturation and Spanish language media to a variety of attitudinal effects, we explore the relationship between linguistic media consumption and political trust and efficacy using three unique datasets: the 2008 CMPS, 2016 CMPS, and our own survey conducted in 2021. We then leverage unique variables in the 2016 CMPS to explore whether Latino trust and efficacy relate directly to relative consumption of Spanish language media or indirectly to Spanish language media through recall of Latino-oriented content and induced emotional reactions.

A Corpus-based Comparison of Lexical Features in English News: China Daily and CNNs Reports about Russia-Ukraine Conflict as Examples

The news plays a crucial role in disseminating information to the public. The use and preferences of vocabulary in news articles reflect the language proficiency, attitudes, and positions of news writers. Therefore, this study examines the differences in vocabulary characteristics between China Daily, a Chinese news organization, and CNN, a US news organization, in their news writing on the Russia-Ukraine conflict. Through corpus-based research methods, the study aims to explore the differences in lexical features and provide insights for journalists and English writing learners in terms of vocabulary selection and comprehension when writing and reading English news about the Russia-Ukraine conflict and related war and conflict events.