A Corpus-Based Critical Discourse Analysis of Trump and Biden Administrations’China Policies  被引量:2

在线阅读下载全文

作  者:ZHI Yongbi YIN Wenjing ZHI Ran 

机构地区:[1]Suzhou University of Science and Technology,Suzhou,China [2]Nanjing Normal University,Nanjing,China

出  处:《International Relations and Diplomacy》2022年第4期175-189,共15页国际关系与外交(英文版)

基  金:2022年度江苏省研究生科研创新项目,项目批准号:KYCX22_1477;苏州科技大学城市发展智库;苏州科技大学国外智库涉华舆情分析研究中心。

摘  要:The theory of proximization is an effective discourse strategy to study the speaker’s ability to achieve his own legitimacy or reinforce the other’s illegitimacy,and its superiority can be maximized by means of quantitative and comparative analysis.In this study,we collected reports on Trump’s and Biden’s policies on China to build two small corpora,with a total of 11,030 words in the Trump corpus and 17,566 words in the Biden corpus.The critical discourse analysis is combined with proximization theory.With the help of BFSU Qualitative Coder 1.2,Antconc 3.5.7,and Log-Likelihood and Chi-Square Calculator 1.0,a critical cognitive score of the relevant discourse was conducted from the perspective of proximization theory.It has been found that:(1)Both Trump and Biden administrations resort to a large number of spatial proximization strategies to build ODCs converging to IDCs with China as the ODC,posing a threat to internal physical IDCs;(2)in the use of temporal proximization strategy,both administrations use primarily modal verbs and various entities to construct ODCs that extend indefinitely into the present and future,emphasizing the urgency and the threat of the effect and reinforcing the legitimacy of their actions;(3)in terms of axiological proximization strategy,the two administrations differ greatly from each other,indicating that there are still discursive biases.

关 键 词:proximization theory critical discourse analysis American policies toward China CORPUS the U.S.government documents 

分 类 号:H31[语言文字—英语]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象