[Paper Review] Visible Insights of the Invisible Pandemic: A Scientometric, Altmetric and Topic Trend Analysis

Sujit Bhattacharya, Shubham Singh|arXiv (Cornell University)|Apr 22, 2020

COVID-19 epidemiological studies18 references12 citations

TL;DR

This study conducts a scientometric, altmetric, and topic trend analysis of early COVID-19 research to identify influential papers, key research topics, and public perception trends. By analyzing scholarly output and online discourse, it reveals dominant research themes and societal concerns, offering insights into the evolving knowledge landscape during the pandemic's initial phase.

ABSTRACT

The recent SARS-COV-2 virus outbreak has created an unprecedented global health crisis! The disease is showing alarming trends with the number of people getting infected with this disease, new cases and death rate are all highlighting the need to control this disease at the earliest. The strategy now for the governments around the globe is how to limit the spread of the virus until the research community develops treatment/drug or vaccination against the virus. The outbreak of this disease has unsurprisingly led to huge volume of research within a short period of time surrounding this disease. It has also led to aggressive social media activity on twitter, Facebook, dedicated blogs, news reports and other online sites actively involved in discussing about the various aspects of and related to this disease. It becomes a useful and challenging exercise to draw from this huge volume of research, the key papers that form the research front, its influence in the research community, and other important research insights. Similarly, it becomes important to discern the key issues that influence the society concerning this disease. The paper is motivated by this. It attempts to distinguish which are the most influential papers, the key knowledge base and major topics surrounding the research covered by COVID-19. Further it attempts to capture the society's perception by discerning key topics that are trending online. The study concludes by highlighting the implications of this study.

Motivation & Objective

• To identify the most influential scientific papers in the early phase of the COVID-19 pandemic using scientometric indicators.
• To map the evolving research frontiers and dominant knowledge domains in COVID-19 literature.
• To analyze public engagement and societal perception by examining trending topics in social media and online platforms.
• To integrate scientometric, altmetric, and topic modeling techniques to provide a multidimensional view of pandemic-related research.
• To offer actionable insights for researchers, policymakers, and public health officials on knowledge dissemination and research priorities.

Proposed method

• Conducted a comprehensive bibliometric analysis of COVID-19-related scholarly publications from early 2020.
• Applied altmetric scores to assess the online visibility and public engagement of research papers.
• Employed topic modeling techniques to extract and categorize dominant research themes from the literature.
• Mapped temporal trends in research output and topic prevalence to identify emerging and declining research areas.
• Correlated scientometric indicators (e.g., citation counts) with altmetric scores to assess influence across academic and public spheres.
• Used data from arXiv and other open-access repositories to ensure broad coverage of early pandemic research.

Experimental results

Research questions

• RQ1 Which scientific papers on COVID-19 were most influential in the early stages of the pandemic?
• RQ2 What are the dominant research topics and thematic clusters in the initial wave of COVID-19 literature?
• RQ3 How do altmetric scores correlate with traditional scientometric indicators like citations?
• RQ4 What are the most discussed topics in public online discourse related to COVID-19?
• RQ5 How do research trends and public perception align or diverge during the early pandemic phase?

Key findings

• The study identified a core set of highly cited and widely discussed papers that formed the foundational research front in early COVID-19 science.
• Key research topics included viral transmission dynamics, clinical management, diagnostic methods, and public health interventions.
• A strong correlation was observed between high altmetric scores and papers with significant public engagement, particularly on platforms like Twitter and news outlets.
• Topic modeling revealed that research on viral pathogenesis and therapeutic interventions were among the most prominent thematic clusters.
• Papers with high altmetric scores often addressed public health implications and were more likely to be covered in mainstream media.
• The analysis highlighted a rapid shift in research focus from virology and diagnostics to treatment and vaccine development within the first few months.