This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2388) Digital Science, Open Science (69) Epublishing and Open Access (80) Outbreak and Pandemic Preparedness and Management (1673) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1482)

Published on in Vol 22, No 11 (2020): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21559, first published .
Analysis of Scientific Publications During the Early Phase of the COVID-19 Pandemic: Topic Modeling Study

Analysis of Scientific Publications During the Early Phase of the COVID-19 Pandemic: Topic Modeling Study

Analysis of Scientific Publications During the Early Phase of the COVID-19 Pandemic: Topic Modeling Study

Authors of this article:

Andreas Älgå1, 2 Author Orcid Image ;   Oskar Eriksson3 Author Orcid Image ;   Martin Nordberg1 Author Orcid Image
Article Authors Cited by (44) Tweetations (11) Metrics

Journals

  1. Chen N, Zhong Z, Pang J. An Exploratory Study of COVID-19 Information on Twitter in the Greater Region. Big Data and Cognitive Computing 2021;5(1):5 View
  2. Älgå A, Eriksson O, Nordberg M. The development of preprints during the COVID‐19 pandemic. Journal of Internal Medicine 2021;290(2):480 View
  3. Li W, Sun K, Zhu Y, Song J, Yang J, Qian L, Wang S. Analyzing the Research Evolution in Response to COVID-19. ISPRS International Journal of Geo-Information 2021;10(4):237 View
  4. Älgå A, Eriksson O, Nordberg M. Authors' Reply to: COVID-19 as a “Force Majeure” for Non–COVID-19 Clinical and Translational Research. Comment on “Analysis of Scientific Publications During the Early Phase of the COVID-19 Pandemic: Topic Modeling Study”. Journal of Medical Internet Research 2021;23(5):e29156 View
  5. Milovanovic P, Dumic I. COVID-19 as a “Force Majeure” for Non–COVID-19 Clinical and Translational Research. Comment on “Analysis of Scientific Publications During the Early Phase of the COVID-19 Pandemic: Topic Modeling Study”. Journal of Medical Internet Research 2021;23(5):e27937 View
  6. Kim O, Drapkina O, Rodionova Y. Russian-language publication activities of medical researchers during the COVID-19 pandemic: results of the year. Russian Journal of Cardiology 2021;26(4):4451 View
  7. Jayadev C. Commentary: Publications boom/boon during COVID-19 – more than meets the eye!. Indian Journal of Ophthalmology 2021;69(5):1249 View
  8. Zengul F, Zengul A, Mugavero M, Oner N, Ozaydin B, Delen D, Willig J, Kennedy K, Cimino J. A critical analysis of COVID-19 research literature: Text mining approach. Intelligence-Based Medicine 2021;5:100036 View
  9. Scarpino I, Zucco C, Vallelunga R, Luzza F, Cannataro M. Investigating Topic Modeling Techniques to Extract Meaningful Insights in Italian Long COVID Narration. BioTech 2022;11(3):41 View
  10. Park S, Lim H, Park J, Choe Y. Impact of COVID-19 Pandemic on Biomedical Publications and Their Citation Frequency. Journal of Korean Medical Science 2022;37(40) View
  11. De La Hoz-M J, Mendes S, Fernández-Gómez M, González Silva Y. Capturing the Complexity of COVID-19 Research: Trend Analysis in the First Two Years of the Pandemic Using a Bayesian Probabilistic Model and Machine Learning Tools. Computation 2022;10(9):156 View
  12. Jiang H, Castellanos A, Castillo A, Gomes P, Li J, VanderMeer D. Nurses’ Work Concerns and Disenchantment During the COVID-19 Pandemic: Machine Learning Analysis of Web-Based Discussions. JMIR Nursing 2023;6:e40676 View
  13. Urru S, Sciannameo V, Lanera C, Salaris S, Gregori D, Berchialla P. A topic trend analysis on COVID-19 literature. DIGITAL HEALTH 2022;8:205520762211336 View
  14. Hoang Y, Ngo V, Bich Vu N. Central bank digital currency: A systematic literature review using text mining approach. Research in International Business and Finance 2023;64:101889 View
  15. Dehghani M, Ebrahimi F. ParsBERT topic modeling of Persian scientific articles about COVID-19. Informatics in Medicine Unlocked 2023;36:101144 View
  16. Jo W, Kim Y, Seo M, Lee N, Park J. Online information analysis on pancreatic cancer in Korea using structural topic model. Scientific Reports 2022;12(1) View
  17. Al Harthi H, Al Fannah J, Khamis F, Al Hashmi S, Al Syiabi B, Al Habsi A, Al-Maniri A, Al Salmi Q, Al Awaidy S. Oman's COVID-19 publication trends: A cross-sectional bibliometric study. Public Health in Practice 2022;4:100310 View
  18. Zhou X, Chen C, Yao Y, Xia J, Cao L, Qin X. The scar that takes time to heal: A systematic review of COVID-19-related stigma targets, antecedents, and outcomes. Frontiers in Psychology 2022;13 View
  19. Chillakuru Y, Gerhard E, Shim T, Selesnick S, Lustig L, Krouse J, Hanna E, Smith T, Fisher E, Kerschner J, Monfared A. Impact of COVID‐19 on Otolaryngology Literature. The Laryngoscope 2022;132(7):1364 View
  20. Heo S, Chan A, Diaz Peralta P, Jin L, Pereira Nunes C, Bell M. Impacts of the COVID-19 pandemic on scientists’ productivity in science, technology, engineering, mathematics (STEM), and medicine fields. Humanities and Social Sciences Communications 2022;9(1) View
  21. Prabha S, Sardana N. Question Tags or Text for Topic Modeling: Which is better. Procedia Computer Science 2023;218:2172 View
  22. Luo J, Chai M, Pan X. Identification of Research Priorities during the COVID-19 Pandemic: Implications for Its Management. International Journal of Environmental Research and Public Health 2021;18(24):13105 View
  23. Zarindast A, Sharma A, Wood J. Application of text mining in smart lighting literature - an analysis of existing literature and a research agenda. International Journal of Information Management Data Insights 2021;1(2):100032 View
  24. Skarpa P, Garoufallou E. The plethora of information and individuals’ perceived feelings during COVID-19 pandemic in Greece. Global Knowledge, Memory and Communication 2024;73(4/5):538 View
  25. Yatcilla J, Young S. Library Responses During the Early Days of the Pandemic: A Bibliometric Study of the 2020 LIS Literature. Journal of Library Administration 2021;61(8):964 View
  26. Lee J, Kim Y, Han D. LDA-based topic modeling for COVID-19-related sports research trends. Frontiers in Psychology 2022;13 View
  27. Chin H, Lima G, Shin M, Zhunis A, Cha C, Choi J, Cha M. User-Chatbot Conversations During the COVID-19 Pandemic: Study Based on Topic Modeling and Sentiment Analysis. Journal of Medical Internet Research 2023;25:e40922 View
  28. Dastani M, Danesh F, Nazir S. Iranian COVID-19 Publications in LitCovid: Text Mining and Topic Modeling. Scientific Programming 2021;2021:1 View
  29. Sittar A, Major D, Mello C, Mladenic D, Grobelnik M. Political and Economic Patterns in COVID-19 News: From Lockdown to Vaccination. IEEE Access 2022;10:40036 View
  30. Dastani M, Ghorbani M. Bibliometric and Text Mining Analysis on COVID-19 Research Projects in Iran. Depiction of Health 2021;12(4):333 View
  31. Zhang Y, Li H, Mao J, He G, Yang Y, Jiang Z, Duan Y. COVID-19: a disruptive impact on the knowledge support of references. Scientometrics 2023;128(8):4791 View
  32. Whittle E, Novotny M, McCaul S, Moeller F, Junk M, Giraldo C, O'Gorman M, de Chenu C, Dzavan P. Application of machine learning models to animal health pharmacovigilance: A proof‐of‐concept study. Journal of Veterinary Pharmacology and Therapeutics 2023;46(6):393 View
  33. Storey V, Lukyanenko R, Castellanos A. Conceptual Modeling: Topics, Themes, and Technology Trends. ACM Computing Surveys 2023;55(14s):1 View
  34. Danesh F, Dastani M. Text classification technique for discovering country-based publications from international COVID-19 publications. DIGITAL HEALTH 2023;9 View
  35. Kalinauskas M, Shuhani Y, Pinto L, Inácio M, Pereira P. Mapping ecosystem services in protected areas. A systematic review. Science of The Total Environment 2024;912:169248 View
  36. Fu W, Akbar S. Expert Profile Identification From Community Detection on Author-Publication-Keyword Graph With Keyword Extraction. IEEE Access 2024;12:27918 View
  37. Li Y, Chen M, Lee H. Health communication on social media at the early stage of the pandemic: Examining health professionals’ COVID-19 related tweets. Social Science & Medicine 2024;347:116748 View
  38. Chandrabhatla A, Narahari A, Horgan T, Patel P, Sturek J, Davis C, Jackson P, Bell T. Machine Learning-based Analysis of Publications Funded by the National Institutes of Health's Initial COVID-19 Pandemic Response. Open Forum Infectious Diseases 2024;11(4) View
  39. Li J, Wang S, Rudinac S, Osseyran A. High-performance computing in healthcare: An automatic literature analysis perspective. Journal of Big Data 2024;11(1) View
  40. Hagerman L, Clark E, Neil-Sztramko S, Colangeli T, Dobbins M. Features of databases that supported searching for rapid evidence synthesis during COVID-19: implications for future public health emergencies. BMC Medical Research Methodology 2024;24(1) View

Books/Policy Documents

  1. Lezama Sánchez A, Tovar Vidal M, Reyes-Ortiz J. Proceedings of the Future Technologies Conference (FTC) 2022, Volume 3. View
  2. Cunningham J. The COVID-19 Crisis and Entrepreneurship. View