Bibliometric Coupling Analysis of COVID-19 Literature
A Bibliographic coupling analysis examines the reference lists of documents, to identify where articles share a common reference. The degree of overlap between article’s reference list represents the strength of the connection between them. Greater overlap means two documents share a large proportion of references, and thus a probability that the content are on related topics. Conversely, little overlap indicates the documents are based on distinct pieces of literature, with few commonalities.
For more information about what a bibliometric coupling analysis is, please see the about page.
Applications for the bibliometric coupling results:
- Organizes published articles by topics, enables the reader to identify articles within an area of interest.
- It is a complementary way to identify related research. The results are not based on search terms, so identifying related articles through this method opens the possibility to make valuable and novel connections between research articles.
To access the interactive map, you need to open the graph in VosViewer, which allows you to search the map, see article information on each node in the graph diagram, and by clicking on the node, open the article in a browser window. To open the map in VOSviewer, please download the free program: VOSviewer here, and open the files.
Insights and trends
When we initiated this project in mid-March 2020, there were 296 documents on COVID-19 in Scopus, of which 197 included the bibliometric information necessary to conduct a coupling analysis. Since then, there has been a sharp increase, and in mid-September, 45638 documents on the pandemic was available in the database.
Coupling analyses on documents from early in the pandemic suggested four topics: 1) The contributions were on “Overview of the new virus”, 2) “Clinical medicine,”, 3) “On the virus,” which included topics ranging from the origin of the virus, its genome, possible therapeutics and early research on these topics, and 4) literature on “Reproduction rate and spread.” For a more detailed description, please see our preprint
In July, we conducted a coupling analysis on journals, creating a network graph showing journals that have published ten or more articles on COVID-19 since March. Of the (then) 4585 journals that had published COVID-19 literature, 706 have published ten or more articles. The analyses showed 5 clusters. In the different clusters, these were the journals with the highest closeness centrality: 1) Diabetes And Metabolic Syndrome: Clinical Research And Reviews, BMJ, and Diabetes Research And Clinical Practice. 2) Science Of The Total Environment, International Journal Of Infectious Diseases, and Lancet. 3) Journal Of Medical Virology, Frontiers In Public Health, and Medical Hypotheses. 4) International Journal Of Environmental Research And Public Health, Sustainability, Brain, Behavior, And Immunity. 5) Jama – Journal Of The American Medical Association, Pediatric Pulmonology, and Frontiers In Pediatrics. For more details, see this post.
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Network Visualization of Bibliometric coupling of COVID-19 meta-analysis
In this post, we analyze the 1622 COVID related articles published up to the 14th of July, with the term Meta-analysis in the title, available in Scopus. We conducted a keyword co-occurrence analysis, and a coupling analysis.
With the vast amounts of research on COVID, and the value in examining the results of multiple studies, meta-analysis are important studies, that generally yield more reliable results, as well as potentially identifying moderators and mechanisms single studies are ill-suited for.
In the keyword co-occurrence analysis, we se the terms group into 9 clusters. We include the top 10 keywords in each cluster in the table below.
Cluster 1 | Cluster 2 | Cluster 3 | Cluster 4 | Cluster 5 | ||||||||||||||
Keyword | Weighted degree | Occurrence | Keyword | Weighted degree | Occurrence | Keyword | Weighted degree | Occurrence | Keyword | Weighted degree | Occurrence | Keyword | Weighted degree | Occurrence | ||||
artificial ventilation | 150 | 3123 | viral pneumonia | 415 | 6741 | mortality | 509 | 7898 | disease severity | 346 | 6797 | virology | 268 | 4516 | ||||
mortality rate | 140 | 2882 | prevalence | 307 | 4870 | risk factor | 299 | 5245 | prognosis | 167 | 3353 | procedures | 139 | 2039 | ||||
treatment outcome | 173 | 2709 | clinical outcome | 138 | 2572 | comorbidity | 226 | 4329 | severity of illness index | 156 | 2963 | quality control | 104 | 1914 | ||||
antivirus agent | 90 | 2084 | risk assessment | 130 | 2211 | hypertension | 168 | 3556 | c reactive protein | 92 | 2701 | isolation and purification | 102 | 1735 | ||||
adult respiratory distress syndrome | 86 | 2048 | epidemiology | 131 | 1771 | diabetes mellitus | 162 | 3353 | blood | 123 | 2533 | nonhuman | 75 | 1541 | ||||
hydroxychloroquine | 82 | 1855 | age | 89 | 1715 | disease association | 163 | 3100 | d-dimer | 76 | 2029 | diagnosis | 90 | 1472 | ||||
drug efficacy | 83 | 1715 | sars | 88 | 1442 | outcome assessment | 133 | 2450 | procalcitonin | 50 | 1556 | children | 82 | 1442 | ||||
drug therapy | 102 | 1500 | cohort analysis | 62 | 1252 | cardiovascular diseases | 111 | 2306 | biological marker | 67 | 1511 | pathogenicity | 64 | 1401 | ||||
antiviral agents | 73 | 1459 | infection risk | 70 | 1243 | mortality risk | 77 | 1429 | laboratory test | 51 | 1459 | reverse transcription polymerase chain reaction | 58 | 1100 | ||||
lopinavir plus ritonavir | 46 | 1447 | medline | 60 | 1190 | retrospective study | 72 | 1371 | lactate dehydrogenase | 48 | 1449 | real time polymerase chain reaction | 51 | 996 | ||||
drug safety | 68 | 1429 | major clinical study | 55 | 1074 | newcastle-ottawa scale | 74 | 1337 | interleukin 6 | 56 | 1414 | immunology | 47 | 968 | ||||
drug effect | 71 | 1299 | sex difference | 52 | 1029 | chronic obstructive lung disease | 52 | 1315 | metabolism | 63 | 1360 | genetics | 43 | 850 | ||||
corticosteroids | 50 | 1241 | adolescent | 53 | 981 | disease course | 57 | 1178 | disease exacerbation | 61 | 1336 | clinical laboratory techniques | 36 | 816 | ||||
azithromycin | 46 | 1222 | health care personnel | 59 | 858 | malignant neoplasm | 45 | 1176 | biomarkers | 57 | 1253 | laboratory technique | 36 | 816 | ||||
chloroquine | 47 | 1080 | practice guideline | 43 | 836 | very elderly | 55 | 1106 | lymphocyte count | 45 | 1212 | diagnostic accuracy | 29 | 527 | ||||
Cluster 6 | Cluster 7 | Cluster 8 | Cluster 9 | |||||||||||||||
Keyword | Weighted degree | Occurrence | Keyword | Weighted degree | Occurrence | Keyword | Weighted degree | Occurrence | Keyword | Weighted degree | Occurrence | |||||||
intensive care units | 219 | 4354 | fever | 124 | 3250 | diarrhea | 87 | 2179 | pathophysiology | 115 | 2198 | |||||||
complication | 233 | 3744 | clinical features | 121 | 2951 | aspartate aminotransferase | 62 | 1759 | headache | 50 | 1319 | |||||||
hospitalization | 178 | 3609 | coughing | 105 | 2724 | alanine aminotransferase | 58 | 1677 | cerebrovascular disease | 45 | 1087 | |||||||
hospital admission | 121 | 2476 | dyspnea | 83 | 2409 | vomiting | 48 | 1314 | cerebrovascular accident | 30 | 682 | |||||||
incidence | 130 | 2316 | fatigue | 67 | 1915 | nausea | 45 | 1231 | hospital discharge | 33 | 636 | |||||||
hospital mortality | 69 | 1331 | ct | 83 | 1666 | abdominal pain | 42 | 1056 | dizziness | 18 | 555 | |||||||
hospital patient | 64 | 1277 | myalgia | 53 | 1496 | bilirubin | 31 | 1004 | anosmia | 28 | 426 | |||||||
acute kidney failure | 52 | 1167 | lymphocytopenia | 46 | 1399 | gastrointestinal symptom | 39 | 924 | nausea and vomiting | 15 | 407 | |||||||
intensive care | 49 | 1001 | pathology | 75 | 1333 | thrombocytopenia | 37 | 850 | neurologic disease | 20 | 334 | |||||||
heart injury | 39 | 947 | pneumonia | 57 | 1240 | liver disease | 36 | 808 | smelling disorder | 23 | 311 | |||||||
critical illness | 44 | 779 | sore throat | 35 | 1168 | anorexia | 22 | 698 | brain ischemia | 13 | 273 | |||||||
invasive ventilation | 31 | 690 | diagnostic imaging | 50 | 993 | liver injury | 31 | 650 | brain hemorrhage | 12 | 261 | |||||||
acute kidney injury | 38 | 609 | infant | 40 | 953 | aspartate aminotransferase blood level | 17 | 561 | ageusia | 12 | 252 | |||||||
lung embolism | 30 | 595 | pregnancy | 46 | 846 | alanine aminotransferase blood level | 15 | 503 | olfaction disorders | 17 | 219 | |||||||
heart arrhythmia | 26 | 577 | symptoms | 37 | 786 | gastrointestinal disease | 27 | 486 | taste disorder | 13 | 216 |
The coupling analysis gives a similar clustering. If you open the map in VOSviewer, it is possible to click on individual studies, see which the are closely linked to, and open the paper directly in a browser.
VOSViewer files:
To open the map directly in VOSviewer, please use the coupling MAP and NET files from December 1st, available through the Open Science Foundation (OSF) repository:
https://osf.io/54gqw/
Network Visualization of Bibliometric Co-Citation Analysis of COVID-19 Literature, based on a sample of publications in January 2021
In this post, we analyze the newest 2000 articles available in Scopus at the start of feburary. we conducted a co-citation analysis, with minimum 50 citation of a given journal, with minimum of 500 co-citations between two journals to show the link.
VOSViewer files:
To open the map directly in VOSviewer, please use the coupling MAP and NET files from December 1st, available through the Open Science Foundation (OSF) repository:
https://osf.io/54gqw/