@inproceedings{mccarthy-etal-2021-mixed,
title = "A Mixed-Methods Analysis of Western and {H}ong {K}ong{--}based Reporting on the 2019{--}2020 Protests",
author = "McCarthy, Arya D. and
Scharf, James and
Dore, Giovanna Maria Dora",
editor = "Degaetano-Ortlieb, Stefania and
Kazantseva, Anna and
Reiter, Nils and
Szpakowicz, Stan",
booktitle = "Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature",
month = nov,
year = "2021",
address = "Punta Cana, Dominican Republic (online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.latechclfl-1.20/",
doi = "10.18653/v1/2021.latechclfl-1.20",
pages = "178--188",
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 \textit{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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%0 Conference Proceedings
%T A Mixed-Methods Analysis of Western and Hong Kong–based Reporting on the 2019–2020 Protests
%A McCarthy, Arya D.
%A Scharf, James
%A Dore, Giovanna Maria Dora
%Y Degaetano-Ortlieb, Stefania
%Y Kazantseva, Anna
%Y Reiter, Nils
%Y Szpakowicz, Stan
%S Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic (online)
%F mccarthy-etal-2021-mixed
%X 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.
%R 10.18653/v1/2021.latechclfl-1.20
%U https://aclanthology.org/2021.latechclfl-1.20/
%U https://doi.org/10.18653/v1/2021.latechclfl-1.20
%P 178-188
Markdown (Informal)
[A Mixed-Methods Analysis of Western and Hong Kong–based Reporting on the 2019–2020 Protests](https://aclanthology.org/2021.latechclfl-1.20/) (McCarthy et al., LaTeCHCLfL 2021)
ACL