ArticleScientometrics2021
Understanding the temporal evolution of COVID-19 research through machine learning and natural language processing.
Article in Scientometrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed, 3 citations in OpenAlex.
- Thematic Evolution in Medical Education Research (2000-2024): A Large-Scale BERTopic Analysis.Advances in medical education and practice · 2026Review
- TASCI: transformers for aspect-based sentiment analysis with contextual intent integration.PeerJ. Computer science · 2025Article
- Evolving techniques in sentiment analysis: a comprehensive review.PeerJ. Computer science · 2025Article
- Analysis of learning curves in predictive modeling using exponential curve fitting with an asymptotic approach.PloS one · 2024Article
- Do Scholars Respond Faster Than Google Trends in Discussing COVID-19 Issues? An Approach to Textual Big Data.Health data science · 2024Article
- An embedding approach for analyzing the evolution of research topics with a case study on computer science subdomains.Scientometrics · 2023Article
- Predicting Emerging Themes in Rapidly Expanding COVID-19 Literature With Unsupervised Word Embeddings and Machine Learning: Evidence-Based Study.Journal of medical Internet research · 2022Article
- Introducing AI to the molecular tumor board: one direction toward the establishment of precision medicine using large-scale cancer clinical and biological information.Experimental hematology & oncology · 2022Review
- Deep forecasting of translational impact in medical research.Patterns (New York, N.Y.) · 2022Article
- Article
- An Emotional Analysis Method for the Analysis of Cognitive and Psychological Factors in the Change of Second Language Learning Model of Chinese Mainland Students in the Post-epidemic Era.Frontiers in psychology · 2022Article
- Discovering temporal scientometric knowledge in COVID-19 scholarly production.Scientometrics · 2022Article
- Between panic and motivation: did the first wave of COVID-19 affect scientific publishing in Mediterranean countries?Scientometrics · 2022Article
- Spotlight on Early COVID-19 Research Productivity: A 1-Year Bibliometric Analysis.Frontiers in public health · 2022Article
- Review
- Evolutionary warning system for COVID-19 severity: Colony predation algorithm enhanced extreme learning machine.Computers in biology and medicine · 2021Article
- Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing.Yearbook of medical informatics · 2021Review
- Human mobility behavior in COVID-19: A systematic literature review and bibliometric analysis.Sustainable cities and society · 2021Article
- Evolution and structure of research fields driven by crises and environmental threats: the COVID-19 research.Scientometrics · 2021Article
- Trends in COVID-19 Publications: Streamlining Research Using NLP and LDA.Frontiers in digital health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The outbreak of the novel coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been continuously affecting human lives and communities around the world in many ways, from cities under lockdown to new social experiences. Although in most cases COVID-19 results in mild illness, it has drawn global attention due to the extremely contagious nature of SARS-CoV-2. Governments and healthcare professionals, along with people and society as a whole, have taken any measures to break the chain of transition and flatten the epidemic curve. In this study, we used multiple data sources, i.e., PubMed and ArXiv, and built several machine learning models to characterize the landscape of current COVID-19 research by identifying the latent topics and analyzing the temporal evolution of the extracted research themes, publications similarity, and sentiments, within the time-frame of January-May 2020. Our findings confirm the types of research available in PubMed and ArXiv differ significantly, with the former exhibiting greater diversity in terms of COVID-19 related issues and the latter focusing more on intelligent systems/tools to predict/diagnose COVID-19. The special attention of the research community to the high-risk groups and people with complications was also confirmed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.