Liu Yufeng, Tay Dennis
Department of Chinese and Bilingual Studies, The Hong Kong Polytechnic University, Hong Kong, PRC.
Department of English and Communication, The Hong Kong Polytechnic University, Hong Kong, PRC.
Lingua. 2023 Apr;286:103490. doi: 10.1016/j.lingua.2023.103490. Epub 2023 Feb 3.
Previous studies have compared Covid metaphors across languages and national contexts, but seldom focus on the translation issue where news narratives of the same event may be different when translated for different readers. Another unexplored question is whether, and how, successive discursive observations across time in such narratives are related. To fill these gaps, this study employs the Box-Jenkins time series analysis (TSA) method to investigate whether and how WAR metaphor usage in Chinese-English COVID-19 news reports (source articles and their translations) can be fitted with ARIMA (Autoregressive Integrated Moving Average) models. These reports come from three different sources across the year 2020: the Chinese (GT), the American (NYT) and the British (TE). Results show that WAR metaphors in the source news of GT and TE are modelable with an autoregressive and moving average model. However, no models were found to fit their translation counterparts. By contrast, WAR metaphors in both NYT's source and translated news were not modelable. These differences are further qualitatively analyzed with examples in context. The study may contribute to the existing debates on WAR frames in COVID-19 discourse by adding a translation and TSA angle.
以往的研究比较了不同语言和国家背景下关于新冠疫情的隐喻，但很少关注翻译问题，即同一事件的新闻叙事在为不同读者翻译时可能会有所不同。另一个未被探讨的问题是，此类叙事中随时间推移的连续话语观察是否相关以及如何相关。为了填补这些空白，本研究采用Box-Jenkins时间序列分析（TSA）方法，以调查汉英新冠疫情新闻报道（原文及其译文）中战争隐喻的使用能否拟合自回归积分滑动平均（ARIMA）模型。这些报道来自2020年的三个不同来源：中国的（《环球时报》）、美国的（《纽约时报》）和英国的（《经济学人》）。结果表明，《环球时报》和《经济学人》原文新闻中的战争隐喻可用自回归滑动平均模型建模。然而，未发现有模型能拟合其译文。相比之下，《纽约时报》原文和译文新闻中的战争隐喻均无法建模。通过上下文示例对这些差异进行了进一步的定性分析。本研究可能通过增加翻译和时间序列分析的角度，为新冠疫情话语中关于战争框架的现有辩论做出贡献。
