@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://preview.aclanthology.org/jlcl-multiple-ingestion/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."
}