What is it about?
In the face of the unprecedented COVID-19 pandemic, various government-led initiatives and individual actions (e.g., lockdowns, social distancing, and masking) have resulted in diverse pandemic experiences. This study aims to explore these varied experiences to inform more proactive responses for future public health crises. Employing a novel “big-thick” data approach, we analyze and compare key pandemic-related topics that have been disseminated to the public through newspapers with those collected from the public via interviews. Specifically, we utilized 82,533 U.S. newspaper articles from January 2020 to December 2021 and supplemented this “big” dataset with “thick” data from interviews and focus groups for topic modeling. Identified key topics were contextualized, compared and visualized at different scales to reveal areas of convergence and divergence. We found seven key topics from the “big” newspaper dataset, providing a macro-level view that covers public health, policies and economics. Conversely, three divergent topics were derived from the “thick” interview data, offering a micro-level view that focuses more on individuals’ experiences, emotions and concerns. A notable finding is the public’s concern about the reliability of news information, suggesting the need for further investigation on the impacts of mass media in shaping the public’s perception and behavior. Overall, by exploring the convergence and divergence in identified topics, our study offers new insights into the complex impacts of the pandemic and enhances our understanding of key issues both disseminated to and resonating with the public, paving the way for further health communication and policy-making.
Featured Image
Photo by Obi - @pixel9propics on Unsplash
Why is it important?
The COVID-19 pandemic was the first of its kind, in the sense that all people around the world have experienced its impacts. This has resulted in the perennial discussion around physical and mental health problems, social connection disruption, economic loss and increased inequalities which are clear examples of the unprecedented consequences of the pandemic. To prevent the spread of COVID-19 in society, governments globally have implemented a range of top-down measures, including border closures, lockdowns, mandates for wearing masks and social distancing. At the same time, from an individual level different bottom-up approaches have also been applied and adopted, such as vaccine uptake, the adoption of top-down measures (e.g., masking) and community engagement to support local actions. These approaches have resulted in a diverse array of community experiences, influenced by individuals’ life situations, places where they were, and the ways in which information was disseminated or communicated by public health officials. This raises the question on how can we learn from those different experiences? Understanding this is crucial for us to move forward and be relatively more proactive in our response to new emerging public health crises as opposed to being reactive. To this end, this paper aims to uncover the key topics surrounding the pandemic that have been disseminated to the public and delves into major discussions about the pandemic experiences from the public, as well as investigating the potential connections between these two aspects.
Perspectives
This study represents a novel effort in employing a “big-thick” data approach within the context of the COVID-19 pandemic. This novel methodological synergy has proven its power in uncovering insights into the complex and multifaceted nature of the pandemic’s impacts. Through the analysis of newspapers, we gained direct access to the practical issues and broad topics prevalent during the pandemic. In contrast, the analysis of interviews offered a contextual depth from the human-centric perspective, revealing the nuanced experiences and perceptions of individuals. By exploring both the areas of convergence and divergence in these topics, our study enhances the understanding of key issues that both disseminated to and resonate with the public. Overall, this study not only contributes valuable insights to the study of public health during the pandemic but also extends its implication to public health research at large, paving the way for future health communication and policy-making.
Qingqing Chen
University at Buffalo - The State University of New York
Read the Original
This page is a summary of: From print to perspective: A mixed-method analysis of the convergence and divergence of COVID-19 topics in newspapers and interviews, PLOS Digital Health, February 2025, PLOS,
DOI: 10.1371/journal.pdig.0000736.
You can read the full text:
Resources
- Related Content
A comparison between online social media discussions and vaccination rates: A tale of four vaccines
The recent COVID-19 pandemic has brought the debate around vaccinations to the forefront of public discussion. In this discussion, various social media platforms have a key role. While this has long been recognized, the way by which the public assigns attention to such topics remains largely unknown. Furthermore, the question of whether there is a discrepancy between people's opinions as expressed online and their actual decision to vaccinate remains open. To shed light on this issue, in this paper we examine the dynamics of online debates among four prominent vaccines (i.e., COVID-19, Influenza, MMR, and HPV) through the lens of public attention as captured on Twitter in the United States from 2015 to 2021. We then compare this to actual vaccination rates from governmental reports, which we argue serve as a proxy for real-world vaccination behaviors. Our results demonstrate that since the outbreak of COVID-19, it has come to dominate the vaccination discussion, which has led to a redistribution of attention from the other three vaccination themes. The results also show an apparent discrepancy between the online debates and the actual vaccination rates. These findings are in line with existing theories, that of agenda-setting and zero-sum theory. Furthermore, our approach could be extended to assess the public's attention toward other health-related issues, and provide a basis for quantifying the effectiveness of health promotion policies.
- Related Content
Analyzing the vaccination debate in social media data Pre- and Post-COVID-19 pandemic
The COVID-19 virus has caused and continues to cause unprecedented impacts on the life trajectories of millions of people globally. Recently, to combat the transmission of the virus, vaccination campaigns around the world have become prevalent. However, while many see such campaigns as positive (e.g., protecting lives), others see them as negative (e.g., the side effects that are not fully understood scientifically), resulting in diverse sentiments towards vaccination campaigns. In addition, the diverse sentiments have seldom been systematically quantified let alone their dynamic changes over space and time. To shed light on this issue, we propose an approach to analyze vaccine sentiments in space and time by using supervised machine learning combined with word embedding techniques. Taking the United States as a test case, we utilize a Twitter dataset (approximately 11.7 million tweets) from January 2015 to July 2021 and measure and map vaccine sentiments (Pro-vaccine, Anti-vaccine, and Neutral) across the nation. In doing so, we can capture the heterogeneous public opinions within social media discussions regarding vaccination among states. Results show how positive sentiment in social media has a strong correlation with the actual vaccinated population. Furthermore, we introduce a simple ratio between Anti and Pro-vaccine as a proxy to quantify vaccine hesitancy and show how our results align with other traditional survey approaches. The proposed approach illustrates the potential to monitor the dynamics of vaccine opinion distribution online, which we hope, can be helpful to explain vaccination rates for the ongoing COVID-19 pandemic.
Contributors
The following have contributed to this page
