Crisis discourse is a significant site for reporting crises and for discursively managing the public’s emotions. Existing studies of this discourse have largely examined how crises are discursively constructed and responded to, with reassurance treated primarily as a function of responses; few have focused on the reassuring potential of the situation itself. This study therefore investigates the discursive strategies through which media reports construe the COVID-19 situation as improving – a form of reassurance grounded in the situation. Using a mixed-methods approach, the data are analyzed with reference to the appraisal framework and the re-/coupling concept in systemic functional linguistics. Situation improvement is achieved discursively by mitigating and inverting negative evaluations of the crisis: negative values are downgraded or recoupled to improvement-oriented targets, which constructs a sense of persistent threat while subtly inviting a more positive reading of the situation. These findings could deepen understanding of the discursive management of crisis and the role of linguistic analysis in illuminating crisis communication and public reassurance in media discourse.
This article investigates the diachronic evolution of the architectural project description (PD), a genre that emerged in the late 19th century to promote completed projects and attract future commissions. Drawing on two corpora—PDs published in brochures (1970–1995) and those published online (1996–2020)—we examine how this genre has changed in terms of structure, multimodal features, and linguistic characteristics. Combining several methods, we conducted a contextual analysis through interviews with practitioners, a multimodal analysis of 60 representative texts, a moves analysis informed by genre theory, and a corpus-driven linguistic study. Our findings reveal significant shifts: PDs have become longer and more promotional, increasingly emphasising collaboration, sustainability, competition and innovation. Linguistic markers such as attitudinal adjectives, verbs with a positive semantic prosody, modal verbs ‘will’ and ‘can’, the pronoun ‘we’, as well as quotations and slogans are more frequent in recent texts, reflecting a rhetorical shift towards self-promotion and branding. Multimodal enhancements, including colour, photography, interactive elements, and navigational tools, are more prevalent in digital PDs. While many of these transformations are linked to the digital medium, they also reflect broader socio-professional shifts: increased competition, the normalisation of marketing practices, and the rise of a neoliberal managerial discourse. Concerns about stylistic homogenisation of the genre emerge. We argue that future research must consider the implications of artificial intelligence, as firms begin to integrate AI tools into design and communication processes, potentially reshaping the genre further.
Within English for Specific Purposes (ESP) assessment, reading tasks represent the linguistic and discourse demands of academic and professional communication. Maintaining parallel assessment materials while preserving the intended meaning presents an ongoing challenge, particularly in large-scale testing contexts where repeated test administrations can lead to item exposure. This study examines the feasibility of automated item paraphrasing for generating linguistically varied versions of reading assessment materials. A transformer-based Text-to-Text Transfer Transformer (T5) model (Raffel et al., 2020) generated reformulated versions of 16 IELTS reading passages and associated comprehension questions drawn from Academic and General Training materials. The original and paraphrased texts were evaluated using surface-level and meaning-level similarity metrics to assess linguistic variation and semantic preservation. Results showed low to moderate surface similarity alongside consistently high semantic alignment across passages and questions, indicating lexical and structural variation while preserving informational content. These results provide preliminary evidence that AI-assisted paraphrasing may support the development of linguistically diverse ESP assessment materials with high semantic alignment. However, the absence of expert review and test-taker performance data limits conclusions regarding content validity and operational equivalence. The study contributes to emerging research on natural language processing technologies for sustainable item pool management in ESP assessment.
