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

Arya D. McCarthy, James Scharf, Giovanna Maria Dora Dore


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.
Anthology ID:
2021.latechclfl-1.20
Volume:
Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic (online)
Venues:
CLFL | EMNLP | LaTeCH | LaTeCHCLfL
SIG:
SIGHUM
Publisher:
Association for Computational Linguistics
Note:
Pages:
178–188
Language:
URL:
https://aclanthology.org/2021.latechclfl-1.20
DOI:
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.latechclfl-1.20.pdf