A Mixed-Methods Analysis of Western and Hong Kong–based Reporting on the 2019–2020 Protests

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Abstract

We apply statistical techniques from natural language processing to Western and Hong Kong–based English language newspaper articles that discuss the 2019–2020 Hong Kong protests of the Anti-Extradition Law Amendment Bill Movement. Topic modeling detects central themes of the reporting and shows the differing agendas toward one country, two systems. Embedding-based usage shift (at the word level) and sentiment analysis (at the document level) both support that Hong Kong–based reporting is more negative and more emotionally charged. A two-way test shows that while July 1, 2019 is a turning point for media portrayal, the differences between western- and Hong Kong–based reporting did not magnify when the protests began; rather, they already existed. Taken together, these findings clarify how the portrayal of activism in Hong Kong evolved throughout the Movement.

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McCarthy, A. D., Scharf, J. A., & Dore, G. M. D. (2021). A Mixed-Methods Analysis of Western and Hong Kong–based Reporting on the 2019–2020 Protests. In 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, LaTeCHCLfL 2021 - Co-located with the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021 - Proceedings (pp. 178–188). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.latechclfl-1.20

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