Publications About COVID-19: A Semantic Analysis On Retracted Articles


  • Hugo Duca Universidade Federal do Rio de Janeiro (UFRJ)
  • Ingrid Pacheco Universidade Federal do Rio de Janeiro (UFRJ)
  • Giseli Rabello Lopes Universidade Federal do Rio de Janeiro (UFRJ)
  • Maria Luiza M. Campos Universidade Federal do Rio de Janeiro (UFRJ)
  • Jonice Oliveira Universidade Federal do Rio de Janeiro (UFRJ)



COVID-19, Retracted Articles, Social Network Analysis, Semantic Web, Linked Data, Ontologies


In a hurry for new discoveries to fight the COVID-19 pandemic, several retracted articles began to appear and be cited as references for other studies. In the present work, social network analysis techniques and linked data were used to assess the influence of retracted articles on those that referred to them. As a result, it was found that the most referred retracted work had 2,745 citations, 7 retracted works refer to others in the same situation, and 82.11% of the references were made after the retraction. In addition, the most used words in the titles were associated with possible treatments for the disease and the countries which had the most referred retracted articles are France and Vietnam.


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How to Cite

Duca, H., Pacheco, I., Lopes, G. R., Campos, M. L. M., & Oliveira, J. (2022). Publications About COVID-19: A Semantic Analysis On Retracted Articles. ISys - Brazilian Journal of Information Systems, 15(1), 22:1–22:25.



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