Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China

Research Article

Analysis on the Image of China's Poverty Alleviation Stories Reported by American Mainstream Media Based on Big Data Critical Discourse Research from The Washington Post

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  • @INPROCEEDINGS{10.4108/eai.17-6-2022.2322662,
        author={Xinwei  Song},
        title={Analysis on the Image of China's Poverty Alleviation Stories Reported by American Mainstream Media Based on Big Data Critical Discourse Research from The Washington Post},
        proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China},
        publisher={EAI},
        proceedings_a={ICIDC},
        year={2022},
        month={10},
        keywords={china; poverty alleviation stories; big data; the washington post; critical discourse analysis; corpus},
        doi={10.4108/eai.17-6-2022.2322662}
    }
    
  • Xinwei Song
    Year: 2022
    Analysis on the Image of China's Poverty Alleviation Stories Reported by American Mainstream Media Based on Big Data Critical Discourse Research from The Washington Post
    ICIDC
    EAI
    DOI: 10.4108/eai.17-6-2022.2322662
Xinwei Song1,*
  • 1: Shandong University
*Contact email: sdusongxinwei23@163.com

Abstract

The period from 2020 to 2021 is a crucial transition period for poverty alleviation stories. During this period, the image of China's poverty alleviation stories in the eyes of American mainstream media has immovability and change. This study uses big data and database technology to obtain the reports of The Washington Post on China's poverty alleviation stories, and uses the three-dimensional framework of CDA as a tool to carry out text analysis, discourse practice analysis and social practice analysis. The study found that the Washington Post's coverage of Poverty alleviation stories in 2020-2021 continued its preference for grammar, text structure, direct speech and indirect speech, and deepened its sentiment in vocabulary.