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.- Anthology ID:
- 2022.lrec-1.310
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 2891–2900
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.310
- DOI:
- Cite (ACL):
- Arya D. McCarthy and Giovanna Maria Dora Dore. 2022. Hong Kong: Longitudinal and Synchronic Characterisations of Protest News between 1998 and 2020. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 2891–2900, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Hong Kong: Longitudinal and Synchronic Characterisations of Protest News between 1998 and 2020 (McCarthy & Dore, LREC 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2022.lrec-1.310.pdf