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The ability of chatbots to produce plausible, human-like responses raises questions about the extent of their similarity with original texts. Using a modified version of Halliday’s clause complexing framework, this study compared 50 abstracts of scientific research articles from Nature with generated versions produced by Bard, ChatGPT, and Poe Assistant. None of the chatbots matched the original abstracts in all categories. The only chatbot that came closest was ChatGPT, but differences in the use of finite adverbial clauses and –ing elaborating clauses were detected. Incorporating distinct grammatical features in the algorithms of AI-detection tools is crucially needed to enhance the reliability of their results. A genre-based approach to detecting AI-generated content is recommended.

This paper examines the thematic structure of a corpus of insults using the inference-boundary model of Theme and Rheme. It focuses on the concept of negative inference—which must be generated for an insult to be successfully delivered—and shows how it allows us to better understand and characterize the form that insults generally take. The analysis suggests that insults are typically structured to generate backward-looking negative inferences from the decoder, much in line with how new information (in this case, the thrust of the insult) is generally located in final position. The paper also proposes a summary statement capturing the general configuration of insults and suggestions for further research.

The proliferation of automated paraphrasing tools (APTs) raises questions about how generated paraphrases differ from the original texts. In this study, 50 abstracts published in Nature were compared with paraphrases generated by QuillBot, Jasper, and Copilot. Tactic and logico-semantic relations were analyzed using a modified version of the Hallidayan clause-complexing framework. The findings revealed that the APT that most closely matched Nature was QuillBot; no significant differences were found in any of the categories. Collectively, Jasper and Copilot leaned toward clausal complexity, using fewer paratactic extensions and more hypotactic elaborations. This study highlights general features of generated paraphrases that are not commonly addressed in the literature. Explicit paraphrasing instructions are recommended to avert any misuse of APTs.

This paper examines the thematic structure of a corpus of insults using the inference-boundary model of Theme and Rheme. It focuses on the concept of negative inference—which must be generated for an insult to be successfully delivered—and shows how it allows us to better understand and characterize the form that insults generally take. The analysis suggests that insults are typically structured to generate backward-looking negative inferences from the decoder, much in line with how new information (in this case, the thrust of the insult) is generally located in final position. The paper also proposes a summary statement capturing the general configuration of insults and suggestions for further research.

The ability of chatbots to produce plausible, human-like responses raises questions about the extent of their similarity with original texts. Using a modified version of Halliday’s clause-complexing framework, this study compared 50 abstracts of scientific research articles from Nature with generated versions produced by Bard, ChatGPT, and Poe Assistant. None of the chatbots matched the original abstracts in all categories. The only chatbot that came closest was ChatGPT, but differences in the use of finite adverbial clauses and –ing elaborating clauses were detected. Incorporating distinct grammatical features in the algorithms of AI-detection tools is crucially needed to enhance the reliability of their results. A genre-based approach to detecting AI-generated content is recommended.

Technology-mediated communication cannot help but inform our literacies. This book is a reconceptualization of the role of language and pedagogy in what Kress (2003) has termed the new media age. At the heart of the volume is the notion of 'transformation' - a change in discourse practices, meaning making, technology and, as a result, literacy acquisition itself.The chapters look at language as positioned in a hugely multimodal world. Communication extends beyond the traditional realms of discourse, from the collaborative efforts of wikis to the hybrid speech and text of online messaging. These new areas of meaning-making are excellent and extremely important avenues to explore for academics interested in applied linguistics, language and literature, language acquisition and multimodality.

In the Hallidayan framework, theme and rheme form the message structure of the clause (Halliday & Matthiessen, 2004, p. 64). The patterning of theme and rheme in the text accounts for how the main ideas are structured and developed. The pioneering work of Danes (1970, 1974) on thematic progression (TP) has been particularly valuable in showing how thematic patterning affects the flow and development of the message in various ways. Using the Hallidayan framework (incorporating Danes's TP), 20 essays written by upper secondary school students in Singapore are analyzed for theme and rheme. The good and weak essays in the corpus are compared to find out if there are differences in the way the two groups of writers organise the message structure of their writing. The results show that there is little difference in the selection of theme between the two groups of essays. In terms of TP, however, a striking difference is noted. The good essays are characterised by elaborated developments of theme and rheme. The developments in the weak essays, in contrast, are thin.