Band 2, Heft 2

This study examines the potential of ChatGPT, notable for its skill in standard modern languages, in the context of ancient Chinese. We focus on two fundamental tasks: translating ancient Chinese into modern Chinese and identifying ancient Chinese names. We conduct experiments on Shi Shuo Xin Yu , which is a collection of anecdotes, short conversations, and pithy observations on personalities who lived in China between about 150 and 420 A.D. We also include other methods, like Baidu Yiyan (ERNIE-Bot) for ancient-to-modern translation, and SIKU-RoBERTa for ancient Chinese name recognition. The results reveal that ChatGPT’s performance in ancient Chinese remains in need of enhancement, but it excels in the task of ancient-to-modern translation with the provision of a few context sentences. For the ancient Chinese name recognition, ChatGPT can outperform SIKU-RoBERTa model in terms of precision, but suffers from low recall.

The discrepancies in existing literature regarding the gender/sex effect on voice-emotion mapping have left the nature of the cross-gender differences unclear. To enrich the knowledge of gender differences in acoustic-perceptual mapping in emotional communication, the present study employed an acoustic-integrated approach to investigate how Mandarin speech prosody is perceived by male and female listeners. One hundred native Mandarin participants recognized the affective states and rated the emotional intensity for 4,500 audio files conveying five basic emotional prosody (i.e., anger, joy, sadness, fear, neutrality) from a female speaker. The results showed that females generally identified emotions more accurately and rated them relatively lower in intensity than males. Meanwhile, acoustic-perceptual analysis revealed a higher predictive power of acoustic measures on male performance. The research extends previous findings by showing a general female advantage in emotion detection, especially in high-arousal emotions like anger, joy, and sadness. The current study suggested that the female sensitivity to minimal affective cues should be sourced to a high-level enhancement with a subjective empathetic filter instead of a low-level superiority on objective acoustic sensation. The complicated mechanism of gender differences in emotional communication and the importance of explaining recognition ability with an acoustic-integrated perspective are highlighted.

This study examines the lexical complexity of translated and non-translated chairman’s statements in corporate annual reports through a corpus-based analysis. Drawing on a comprehensive corpus of English chairman’s statements, including both English translations from Chinese and original English texts from the United States and Hong Kong, we analyze various dimensions of lexical complexity. Key measures include lexical diversity, such as the number of different words (NDW) and type-token ratio (TTR) variants, lexical density, and verb sophistication. The results present a nuanced view of lexical complexity in translated texts. Translated chairman’s statements show lower complexity across NDW-related metrics, Corrected TTR, Root TTR, Bi-logarithmic TTR, Uber index, lexical word variation, verb variation, noun variation, and adverb variation. However, they display higher complexity in lexical density and verb sophistication compared to non-translated statements. These findings suggest that while translation may simplify certain aspects of vocabulary use, it can also produce more information-dense texts with more sophisticated verb usage. This paradox challenges traditional views on translation universals and underscores the intricate nature of translated corporate communications.

This research investigates the utilization of the discourse marker (DM) “but” by interviewees (IEs) from a socio-pragmatic standpoint, focusing on its frequency and function through the analysis of a corpus comprising political interviews aired on BBC’s HARDtalk . The IEs are categorized into three demographic cohorts: those from eastern versus western cultures, non-native English-speaking IEs versus native English speakers, and female IEs versus their male counterparts. The study employs both quantitative and qualitative methods. Quantitatively, no statistically significant difference is found in the overall frequency of “but” usage among the three groups. Qualitatively, the analysis reveals the polyfunctionality of the DM “but”, with the most prevalent function being “contrast”, consistently employed across all demographic cohorts, although lacking statistical significance. Additionally, statistically higher usage of various function types is observed among IEs from the western culture and native English speakers compared to their counterparts. Female IEs exhibit a statistically higher frequency in the deployment of the “topic” function than males. Overall, while the frequency and the use of the “contrast” function show no significant difference, the study highlights the nuanced impact of culture, first language, and gender on the multifaceted functions of the DM “but” in political discourse. These findings contribute to our understanding of how socio-pragmatic factors subtly shape the usage of discourse markers like the DM “but” among varied interviewee demographics, as well as its role in shaping public perception and political narratives within the context of political interviews.

This study gives a corpus-assisted discourse study of the framing of climate risks in China Daily (CD) and The New York Times (NYT) to reveal the dynamic relations between risk framing, ideologies, and national interests. The findings show that the risk frame is more favored in NYT. While CD shows more consensus on the risks, NYT emphasizes the disputes over the risks. CD prefers to highlight risks to people and adopt a global frame to underline efforts to address the risks. However, NYT features a national frame and emphasizes the potentially negative impacts on the economy and finance. It tends to show the pessimistic views in facing the threats and thus legitimize the inactions of the US government in the climate control. Their divergences in framing climate risks are further explained in terms of the different functions of the two newspapers and the national interests of the two countries.

In 2020, against the backdrop of the pandemic, climate change and the increasingly tense global situation, Chinese President Xi Jinping delivered a speech at the General Debate of the 75th Session of United Nations General Assembly (UNGA), which attracted extensive media coverage. This research employs corpus-based critical discourse analysis to explore how the Chinese original discourse was mediated by the interpreter and how the interpreter-mediated discourse was further represented and reframed by global news. The lenses of optional shifts and reframing are adopted respectively for intertextual analysis. Results indicate that the interpreter mediates the Statement through explicitation of information, reduction of information, explicitation of logic, and change of voice. Furthermore, the interpreted text and optional shifts within the text are generally well received by global news outlets. However, due to news outlets’ highly selective quotation process and the use of temporal and spatial framing and labelling strategies, the interpreted text may be reframed to construct narratives unexpected by China. This study sheds light on the dynamic process of international communication of diplomatic discourse, during which both the interpreter and global media outlets play crucial roles apart from the source speaker.

This study was motivated by the need to understand the ways users perform speech acts on social media platforms, specifically Twitter, Facebook, and Instagram, and how these acts differ between public and private contexts. The purpose was to analyse the frequencies and types of speech acts (requests, apologies, and compliments) and identify the linguistic and pragmatic strategies employed. Using a mixed-methods research design, a corpus of 3 million posts was collected and analysed. Stratified random sampling ensured a balanced representation of speech acts, and both manual annotation and machine learning techniques were used for classification. Three major findings emerged: first, requests were significantly more frequent and direct in private messages than in public posts across all platforms; second, public apologies were more formal and detailed, while private apologies were concise and personal; third, Instagram had the highest frequency of compliments, with public posts being more explicit and enthusiastic compared to private messages. The study concluded that context and platform-specific features heavily influence communication strategies. These insights advance theoretical understanding and offer practical applications for optimizing social media communication.

This paper examines the representation of child trafficking discourse in online interactions. Data for the study were part of a larger project corpus of 83,815 posts with 1,044,209 tokens collected between July 2023 and May 2024 using the Apify Twitter Scraper. The study adopted a mixed method of corpus-based methodologies and qualitative discourse analysis (QDA). SketchEngine was deployed to quantitatively analyse and track the occurrences of words around child trafficking, while insights drawn from Reisigl and Wodak’s (2009. “The Discourse-Historical Approach.” In Methods of Critical Discourse Analysis . 2nd ed., edited by Ruth Wodak, and Michael Meyer, 87–121. London: Sage) discursive strategies foreground the QDA. Findings reveal that child trafficking discourse manifests two discursive patterns: representation and construction. The former, which captures explicit and implicit depictions through predication and perspectivation strategies, reveals how child trafficking is negatively evaluated as a crisis, crime and evil, and the implicit portrayal of the act as a war. The construction of child trafficking as being downplayed, through intensification and predication strategies, relates to social protest and harsh criticism of the media and political officeholders, and as advocacy along the lines of social movements (e-activism) through hashtags. Thus, the study complements existing knowledge on children’s representation in social media, as online participants’ discourses reinforce awareness-raising, agitation and calls for action.