Abstract
Media has played an important role in public information on COVID-19. But distressing news, e.g., COVID-19 death tolls, may trigger negative emotions in public, discouraging them from following the news, which, in turn, can limit the effectiveness of the media. To understand people’s emotional response to the COVID-19 news, we have investigated the prevalence of basic human emotions in around 19 million user responses to 1.7 million COVID-19 news posts on Twitter from (English-speaking) media across 12 countries from January 2020 to April 2021. We have used Latent Dirichlet Allocation (LDA) to identify news themes on Twitter. Also, the Robustly Optimized BERT Pretraining Approach (RoBERTa) model was used to identify emotions in the tweets. Our analysis of the Twitter data revealed that anger was the most prevalent emotion in user responses to the news coverage of COVID-19. That was followed by sadness, optimism, and joy, steadily over the period of the study. The prevalence of anger (in user responses) was higher for the news about authorities and politics while optimism and joy were more prevalent for the news about vaccination and educational impacts of COVID-19 respectively. The prevalence of sadness in user responses, however, was the highest for the news about COVID-19 cases and deaths and the impacts on the families, mental health, jails, and nursing homes. We also observed a higher level of anger in the user responses to the (COVID-19) news posted by the USA media accounts (e.g., CNN Politics, Fox News, MSNBC). Optimism, on the other hand, was found to be the highest for Filipino media accounts.
Highlights
M EDIA has played a pivotal role in containing the COVID-19 pandemic through public information [1]
We have investigated the emotional responses to the media coverage of the COVID-19 pandemic on Twitter from January 2020 to April 2021 across popular media outlets of 12 countries; the following research questions were formulated: (RQ1): What are the COVID-19 news themes on Twitter? (RQ2): What is the longitudinal distribution of the emotions and themes in the user responses? (RQ3): What is the latitudinal distribution of the emotions and themes in the user responses? (RQ4): What is the distribution of the emotions and themes in the user responses across different media outlets?
We used the Robustly Optimized Bidirectional Encoder Representations from Transformers (BERT) Pretraining Approach (RoBERTa) model to identify the prevalence of basic human emotions in about 19 million user responses corresponding to 1.7 million COVID19 related tweets from official twitter accounts of popular news media from 12 countries between January 2020 to April 2021
Summary
M EDIA has played a pivotal role in containing the COVID-19 pandemic through public information [1]. Others have merely studied the emotions embedded in the COVID-19 news headlines without considering the emotions of the news audience [6, 7]. To overcome these limitations, we have investigated the emotional responses to the media coverage of the COVID-19 pandemic on Twitter from January 2020 to April 2021 across popular media outlets of 12 countries; the following research questions were formulated:. Journalism is becoming more interactive, interconnected, participatory, and global, giving rise to a networked journalism, producing a constant stream of data, and comments [12, 13] While this expands journalists’ reach and influence, it increases their accountability for responsible journalism. Prior research on identifying immediate priorities for research on COVID-19 with a focus on mental health and well-being recognized an urgent need for collecting high-quality data on the mental health and psychological effects of the COVID-19 pandemic across different populations and vulnerable groups [19]
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