Abstract
BackgroundOnline media play an important role in public health emergencies and serve as essential communication platforms. Infoveillance of online media during the COVID-19 pandemic is an important step toward gaining a better understanding of crisis communication.ObjectiveThe goal of this study was to perform a longitudinal analysis of the COVID-19–related content on online media based on natural language processing.MethodsWe collected a data set of news articles published by Croatian online media during the first 13 months of the pandemic. First, we tested the correlations between the number of articles and the number of new daily COVID-19 cases. Second, we analyzed the content by extracting the most frequent terms and applied the Jaccard similarity coefficient. Third, we compared the occurrence of the pandemic-related terms during the two waves of the pandemic. Finally, we applied named entity recognition to extract the most frequent entities and tracked the dynamics of changes during the observation period.ResultsThe results showed no significant correlation between the number of articles and the number of new daily COVID-19 cases. Furthermore, there were high overlaps in the terminology used in all articles published during the pandemic with a slight shift in the pandemic-related terms between the first and the second waves. Finally, the findings indicate that the most influential entities have lower overlaps for the identified people and higher overlaps for locations and institutions.ConclusionsOur study shows that online media have a prompt response to the pandemic with a large number of COVID-19–related articles. There was a high overlap in the frequently used terms across the first 13 months, which may indicate the narrow focus of reporting in certain periods. However, the pandemic-related terminology is well-covered.
Highlights
BackgroundMedia coverage plays an important role in public health emergencies such as the COVID-19 pandemic and serves as a key communication platform during global health crises [1]
This study addressed the following research questions related to the period of the first 13 months of the pandemic: (1) What is the number of COVID-19–related news articles and is this number correlated with the number of new COVID-19 cases? (2) What are the main key terms, the most frequent pandemic-related terms, and the most frequent entities in the focus of the online news media? (3) How has the COVID-19–related content in the online news changed during the first 13 months of the pandemic?
In the period between the two pandemic waves, when the number of cases of infection dropped to zero, the number of publications related to COVID-19 remained high at 43%, despite expectations that the media would write significantly less about COVID-19
Summary
Media coverage plays an important role in public health emergencies such as the COVID-19 pandemic and serves as a key communication platform during global health crises [1]. Recent studies proposed new disease-spreading models integrating media coverage as a strong factor that may influence human behavior in the context of disease transmission [3,4,5]. All of these studies confirm that the media may affect the spread and control of infectious diseases. There were high overlaps in the terminology used in all articles published during the pandemic with a slight shift in the pandemic-related terms between the first and the second waves.
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