This article links media and social movement studies with world society theory to explain cross-national variations in media attention to domestic social protests. We compile a novel large-scale dataset with over 1.2 million protest-related news articles from 12,644 web news sites across 140 countries/areas in 2015–2020. Our cross-national analysis shows that both media- and country-level characteristics explain news coverage of domestic social protests. Our findings show that web news outlets with high web traffic and a propensity to report conflictual events tend to cover more protests. In addition, web news sites in nations with vibrant civil society organizations report more protest events. We also find that there is a positive relationship between online censorship and news coverage in general. But this is driven by news media in democratic countries, and news sites in authoritarian regimes experiencing strong censorship cover fewer protest events. Finally, news media in authoritarian nations with more organizational ties to the international community cover more domestic protests.

The COVID-19 pandemic has led to a global surge in Sinophobia. We examine how Chinese language users responded to COVID-19 on Western social media by compiling a unique database (CNTweets) with over 25 million Chinese tweets mentioning any Chinese characters related to China, the Chinese Communist Party (CCP), Chinese, and Asians from December 2019 to April 2021. Our analysis of Twitter users’ self-reported geographic information shows that most Chinese language users on Twitter originated from Mainland China, Hong Kong, Taiwan, and the United States. We then adopt the Robustly Optimized Bidirectional Encoder Representations from Transformers (RoBERTa) and structural topic modeling to further analyze the sentiments, content, and topics of Chinese tweets during the COVID-19 pandemic. Our results suggest that 61.8% of tweets in our database were contributed by only 1% of Twitter users and 62.2% of tweets were negative toward China. Despite the prevalence of anti-China sentiments, the target entity analysis shows that these negative sentiments were more likely to target the Chinese government and CCP than the Chinese people. Our findings also show that the most popular topics were politics (e.g., Hong Kong protests and Taiwan issues), COVID-19, and the United States (e.g., the US-China relations and domestic issues). Anti-China users focused relatively more on political issues such as democracy and freedom, while pro-China users mentioned cultural and economic topics more. Our social network analysis reveals that these pro-China and anti-China Twitter users lacked in-depth engagement in China-related conversations and were highly segregated from each other. We conclude by discussing our contributions to China and social media studies and possible policy implications.

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