Sui He

Sui He

The growing integration of machine translation into social media platforms is transforming how users interact with each other across cultural and linguistic boundaries. This paper examines user reactions to the launch of Xiaohongshu's built-in translation feature in January 2025. Drawing on a dataset of 6,723 comments collected from 11 official posts promoting the translation function, this paper combines sentiment analysis with thematic analysis to investigate how users perceived and experimented with the function. Results show that reactions were generally positive, particularly for translating posts and comments, although concerns regarding functionality, accessibility, and translation accuracy were also expressed. In addition to evaluative feedback, users actively tested the function with diverse inputs, including words and phrases in English and Chinese, abbreviations in pinyin, internet slang, and other language forms such as emoji, kaomoji, coded texts, etc. The findings highlight the importance of closer collaboration among computer scientists, translation scholars, and platform designers to better understand and improve translation technologies in real world communicative context.

Sui He

Prompt engineering has shown potential for improving translation quality in LLMs. However, the possibility of using translation concepts in prompt design remains largely underexplored. Against this backdrop, the current paper discusses the effectiveness of incorporating the conceptual tool of translation brief and the personas of translator and author into prompt design for translation tasks in ChatGPT. Findings suggest that, although certain elements are constructive in facilitating human-to-human communication for translation tasks, their effectiveness is limited for improving translation quality in ChatGPT. This accentuates the need for explorative research on how translation theorists and practitioners can develop the current set of conceptual tools rooted in the human-to-human communication paradigm for translation purposes in this emerging workflow involving human-machine interaction, and how translation concepts developed in translation studies can inform the training of GPT models for translation tasks.