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Natural Language Processing of COVID-19 Reports Involving China in New York Times —a Machine-based Framing Study of Media Language

Published: 27 June 2023 Publication History

Abstract

Natural Language Processing (NLP) is a most promising and powerful method for big data analysis. It is gaining increasing attention from language researchers with its potentiality in information extraction, automatic indexing, textual framing, topic modeling, sensitivity analysis and other machine analytics studies. Through employing the LDA topic modeling and NLTK (Natural Language Toolkit) Vader SentimentAnalyser, this research makes a contrastive study of the overall news coverage in New York Times (NYT) against the backdrop of Covid-19 and its China-specific reports, with the aim of addressing what areas of concern were respectively selected and foregrounded to the public in these two types, what sensitivities were revealed and how linguistic devices were used to frame China's response to Covid-19. Analysis of metaphorical expressions in NYT shows that metaphors tended to be employed as a device to realize the dominant negative polarity latent in the reports and thus establish unfavourable images of China. This study deepens the methodological endeavors in media and linguistic studies through combining content analysis and machine-based analysis.

References

[1]
Pamela, Shoemaker J., and Stephen D. Reese. 1996. Mediating the Message: Theories of Influences on Media Content. New York: Longman.
[2]
Robert, Entman M. 1993. “Framing: Toward a Clarification of a Fractured Paradigm.” Journal of Communication 43(4): 51-58.
[3]
De Vreese. H., Peter Jochen., and Hollie A. Semetko. 2001. “Framing Politics at the Launch of the Euro: A Cross-national Comparative Study of Frames in the News.” Political Communication 18(2): 107-122.
[4]
Zengjun, Peng. 2004. “Representation of China: An Across Time Analysis of Coverage in the New York Times and Los Angeles Times.” Asian Journal of Communication 14(1): 53-67.
[5]
Catherine, Luther A., and Xiang Zhou. 2005. “Within the Boundaries of Politics: News Framing of SARs in China and the United States.” Journalism & Mass Communication Quarterly 82(4): 857-872.
[6]
Chia-ju, Lin. 2012. “A Textual Analysis of the Coverage of SARS and the Image of China: A Comparative Analysis.” Canadian Center of Science and Education 8(3): 49-62.
[7]
Yuanxin, Wang, and Dehuan, Liu. 2020. “LDA Topic Modeling Analysis for COVID-19 News of Western Mainstream Media from the Perspective of Framing Analysis: An Analysis of New York Times and Guardian Publications.” Advertising Panorama 3:76-89.
[8]
Chan, Li. 2020. “Suffering of Others-A Case Study of Wall Street Journal on How Media Represents China in Covid-19.” International Communications (5): 69-72. 
[9]
Staszak, Jean. F. 2008. “Other/Otherness”. In International Encyclopedia of Human Geography ed. By Rob. Kitchin & Nigel. Thrift (Eds.), Amsterdam: Elsevier.
[10]
Jinping, Gao and Fang Jing. 2020. “An Analysis of China's Publicity Discourse Strategy Transformation in Major Emergencies: Based on the Times Report of the COVID-19 in China.” International Communications 9: 45-47.
[11]
Huimin, Chen, Zeyu, Zhu, Fanchao, Qi, Yining, Ye, Zhiyuan, Liu, Maosong, Sun, and Jianbin, Jin. 2021 “Country Image in COVID-19 Pandemic: A Case Study of China.” IEEE Transactions on Big Data 7(1), 81-92.
[12]
Wei, Mao. 2020 “Discourse Construction and Framing Analysis of Covid-19 Reports in Overseas Media.” Chinese Journalist 4: 82-86.
[13]
Robert, Entman M. 1991. “Framing U.S. Coverage of International News: Contrasts in Narratives of the KAL and Iran Air Incidents.” Journal of Communication 41(4): 6-27.

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  1. Natural Language Processing of COVID-19 Reports Involving China in New York Times —a Machine-based Framing Study of Media Language

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    NLPIR '22: Proceedings of the 2022 6th International Conference on Natural Language Processing and Information Retrieval
    December 2022
    241 pages
    ISBN:9781450397629
    DOI:10.1145/3582768
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Publication History

    Published: 27 June 2023

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    Author Tags

    1. LDA topic modeling
    2. Natural Language Processing
    3. Sensitivity analysis
    4. figurative language
    5. media framing

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