Hong Kong: Longitudinal and Synchronic Characterisations of Protest News between 1998 and 2020

Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022), pages 2891–2900 Marseille, 20-25 June 2022 © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0 2891 Hong Kong: Longitudinal and Synchronic Characterisations of Protest News between 1998 and 2020 Arya D. McCarthy♦ and Giovanna Maria Dora Dore♠ ♦Center for Language and Speech Processing, Johns Hopkins University ♠Krieger School of Arts and Sciences, Johns Hopkins University Abstract This paper showcases the utility and timeliness of the Hong Kong Protest News Dataset, a highly curated collection of news articles from diverse news sources, to investigate longitudinal and synchronic news characterisations of protests in Hong Kong between 1998 and 2020. The properties of the dataset enable us to apply natural language processing to its 4522 articles and thereby study patterns of journalistic practice across newspapers. This paper sheds light on whether depth and/or manner of reporting changed over time, and if so, in what ways, or in response to what. In its focus and methodology, this paper helps bridge the gap between “validity-focused methodological debates” and the use of computational methods of analysis in the social sciences. Keywords: dataset, Hong Kong, news, protests, longitudinal 1. Introduction Protests constitute an important means in contemporary societies by which citizens voice their concerns. How- ever, protests’ ability to communicate their messages and achieve their outcomes depends significantly on whether and how mass media, and especially newspa- pers, portray them (Agnone, 2007; King, 2014). News- papers, in fact, can either amplify and legitimise the protesters’ voices (Gamson and Wolfsfeld, 1993) or marginalise and delegitimise protests by portraying them as dangerous or irrelevant (Boykoff, 2006; Small, 1994). To investigate the dynamic relationship between protests and newspapers, we have constructed the Hong Kong Protest News Dataset, an original collection of news articles covering the occurrence and evolution of protests in Hong Kong between 1998 and 2020. Protest participation has long been an undercurrent in Hong Kong’s political culture (Rawnsley and Rawns- ley, 2002) dating back to British colonial rule, and has evolved from the bloody riots of the 1960s to the protests of 2019–2020, when up to two million peo- ple took to the streets against the proposed amend- ment to the Fugitive Offenders and Mutual Legal As- sistance in Criminal Matters Legislation Bill (ELAB). Hong Kong protests captured the world’s attention with defiant crowds commemorating the 1989 Tiananmen Square incidents, nostalgically marking the transfer of sovereignty from the UK back to China every July 1 since 1997, and students blockading roads for 79 days in the Admiralty district during the pro-democracy Occupy Central protests in 2014 (Weiss and Aspinall, 2012). The news value of these actions grew, as early demon- strations to voice dissent morphed into an increasingly violent anti-government, anti-Beijing movement with demands for greater democracy. To showcase the relevance, utility, and timeliness of the Hong Kong Protest News Dataset in investigating longitudinal and synchronic characterisations of news protests in Hong Kong, we apply natural language pro- cessing (NLP) to study patterns of journalistic practice …

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