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

被引：0

作者：

McCarthy, Arya D. ^{[1
]}

Dore, Giovanna Maria Dora ^{[2
]}

机构：

[1] Johns Hopkins Univ, Ctr Language & Speech Proc, Baltimore, MD 21218 USA

[2] Johns Hopkins Univ, Krieger Sch Arts & Sci, Baltimore, MD 21218 USA

来源：

LREC 2022: THIRTEEN INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION | 2022年

关键词：

dataset; Hong Kong; news; protests; longitudinal; MEDIA;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页码：2891 / 2900

页数：10

共 47 条

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