Quantifying online news media coverage of the COVID-19 pandemic: Text mining study and resource

Konrad Krawczyk*, Tadeusz Chelkowski, Daniel J. Laydon, Swapnil Mishra, Denise Xifara, Seth Flaxman, Seth Flaxman, Thomas Mellan, Veit Schwämmle, Richard Röttger, Johannes T. Hadsund, Samir Bhatt

*Corresponding author for this work

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Abstract

Background: Before the advent of an effective vaccine, nonpharmaceutical interventions, such as mask-wearing, social distancing, and lockdowns, have been the primary measures to combat the COVID-19 pandemic. Such measures are highly effective when there is high population-wide adherence, which requires information on current risks posed by the pandemic alongside a clear exposition of the rules and guidelines in place. Objective: Here we analyzed online news media coverage of COVID-19. We quantified the total volume of COVID-19 articles, their sentiment polarization, and leading subtopics to act as a reference to inform future communication strategies. Methods: We collected 26 million news articles from the front pages of 172 major online news sources in 11 countries (available online at SciRide). Using topic detection, we identified COVID-19–related content to quantify the proportion of total coverage the pandemic received in 2020. The sentiment analysis tool Vader was employed to stratify the emotional polarity of COVID-19 reporting. Further topic detection and sentiment analysis was performed on COVID-19 coverage to reveal the leading themes in pandemic reporting and their respective emotional polarizations. Results: We found that COVID-19 coverage accounted for approximately 25.3% of all front-page online news articles between January and October 2020. Sentiment analysis of English-language sources revealed that overall COVID-19 coverage was not exclusively negatively polarized, suggesting wide heterogeneous reporting of the pandemic. Within this heterogenous coverage, 16% of COVID-19 news articles (or 4% of all English-language articles) can be classified as highly negatively polarized, citing issues such as death, fear, or crisis. Conclusions: The goal of COVID-19 public health communication is to increase understanding of distancing rules and to maximize the impact of governmental policy. The extent to which the quantity and quality of information from different communication channels (eg, social media, government pages, and news) influence public understanding of public health measures remains to be established. Here we conclude that a quarter of all reporting in 2020 covered COVID-19, which is indicative of information overload. In this capacity, our data and analysis form a quantitative basis for informing health communication strategies along traditional news media channels to minimize the risks of COVID-19 while vaccination is rolled out.

Original languageEnglish
Article numbere28253
JournalJournal of Medical Internet Research
Volume23
Issue number6
ISSN1439-4456
DOIs
Publication statusPublished - Jun 2021

Bibliographical note

Publisher Copyright:
©Konrad Krawczyk, Tadeusz Chelkowski, Daniel J Laydon, Swapnil Mishra, Denise Xifara, Seth Flaxman, Seth Flaxman, Thomas Mellan, Veit Schwämmle, Richard Röttger, Johannes T Hadsund, Samir Bhatt.

Keywords

  • COVID-19
  • Infoveillance
  • Public health
  • Sentiment analysis
  • Text mining

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