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Seldom in history does one get a ‘front row seat’—with large-scale dynamic data—on how online news media narratives shift with a global pandemic. News media narratives matter because they shape societal perceptions and influence the core tent poles of our society, from the economy to elections. Given its importance—and with the benefit of hindsight—we provide a systematic framework to analyze news narratives of Covid-19, laying the groundwork to evaluate policy and risk communications.

We leverage a 10-billion-word-database of online news, taken from over 7,000 English newspapers and magazines across 20 countries, culminating in 28 million articles. First, we track the volume of Covid-19 conversations across 20 countries from before to during the pandemic (Oct’19 to May’20). Second, we distill the phases of global pandemic narratives, and elucidate regional differences.

To track the volume of Covid-19 narratives, we identified 10 target terms—Coronavirus, Covid-19, Covid, nCoV, SARS-CoV-2, Wuhan Virus, Virus, Disease, Epidemic, Pandemic—and tracked their combined monthly prevalence across eight months from October 2019 through May 2020. Globally, across 20 countries, we identified 18,042,855 descriptors of the target terms. Further, these descriptors were analysed with natural language processing models to generate the top five topics of Covid-19 that were labelled by two independent researchers. This process was repeated across six continents to distil regional topics.

Our model found four phases of online news media narratives: Pre-pandemic, Early, Peak and …