Published on in Vol 21, No 1 (2019): January

Preprints (earlier versions) of this paper are available at, first published .
The Most Influential Medical Journals According to Wikipedia: Quantitative Analysis

The Most Influential Medical Journals According to Wikipedia: Quantitative Analysis

The Most Influential Medical Journals According to Wikipedia: Quantitative Analysis


  1. Kantarovich D, Vollbrecht H, Cruz S, Castillo H, Lee C, Kushner J, Leng J, Morgan V, Hellman K. Wikipedia: A Medical Student Educational Project to Edit Wikipedia in Preparation for Practicing Evidence-Based Pain Medicine. Journal of Medical Education and Curricular Development 2020;7:238212052095969 View
  2. Smith D, Triberti S. Situating Wikipedia as a health information resource in various contexts: A scoping review. PLOS ONE 2020;15(2):e0228786 View
  3. Lewoniewski W, Węcel K, Abramowicz W. Modeling Popularity and Reliability of Sources in Multilingual Wikipedia. Information 2020;11(5):263 View
  4. Joorabchi A, Doherty C, Dawson J. ‘WP2Cochrane’, a tool linking Wikipedia to the Cochrane Library: Results of a bibliometric analysis evaluating article quality and importance. Health Informatics Journal 2020;26(3):1881 View
  5. Petiška E, Moldan B. Indicator of quality for environmental articles on Wikipedia at the higher education level. Journal of Information Science 2021;47(2):269 View
  6. Masukume G. Why and how medical schools, peer-reviewed journals, and research funders should promote Wikipedia editing. Studies in Higher Education 2020;45(5):984 View
  7. Robert C, Wilson C, Lipton R, Arreto C. Evolution of the Research Literature and the Scientific Community of Alzheimer’s Disease from 1983-2017: A 35-Year Survey. Journal of Alzheimer's Disease 2020;75(4):1105 View
  8. Laurent M. Wikipedia, The Free Online Medical Encyclopedia Anyone Can Plagiarize: Time to Address Wiki-Plagiarism. Publishing Research Quarterly 2020;36(3):399 View
  9. Banasik-Jemielniak N, Jemielniak D, Wilamowski M. Psychology and Wikipedia: Measuring Psychology Journals’ Impact by Wikipedia Citations. Social Science Computer Review 2022;40(3):756 View
  10. Azeroual O, Lewoniewski W. How to Inspect and Measure Data Quality about Scientific Publications: Use Case of Wikipedia and CRIS Databases. Algorithms 2020;13(5):107 View
  11. Inouye K, Mills D. Fear of the academic fake? Journal editorials and the amplification of the 'predatory publishing' discourse. Learned Publishing 2021;34(3):396 View
  12. Chrzanowski J, Sołek J, Fendler W, Jemielniak D. Assessing Public Interest Based on Wikipedia’s Most Visited Medical Articles During the SARS-CoV-2 Outbreak: Search Trends Analysis. Journal of Medical Internet Research 2021;23(4):e26331 View
  13. Konieczny P. From Adversaries to Allies? The Uneasy Relationship between Experts and the Wikipedia Community. She Ji: The Journal of Design, Economics, and Innovation 2021;7(2):151 View
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  15. Hong B, Pollio D, Downs D, Coyne D, North C. Groundhog Day: research without old data and old references. Psychological Medicine 2022;52(4):625 View
  16. Li X, Thelwall M, Mohammadi E. How are encyclopedias cited in academic research? Wikipedia, Britannica, Baidu Baike, and Scholarpedia. El Profesional de la información 2021 View
  17. Lewoniewski W. Identification of Important Web Sources of Information on Wikipedia across various Topics and Languages. Procedia Computer Science 2022;207:3290 View
  18. Arroyo-Machado W, Torres-Salinas D, Costas R. Wikinformetrics: Construction and description of an open Wikipedia knowledge graph data set for informetric purposes. Quantitative Science Studies 2022;3(4):931 View
  19. Zheng X, Chen J, Yan E, Ni C. Gender and country biases in Wikipedia citations to scholarly publications. Journal of the Association for Information Science and Technology 2023;74(2):219 View
  20. Mendes T, Dawson J, Evenstein Sigalov S, Kleiman N, Hird K, Terenius O, Das D, Geres N, Azzam A. Wikipedia in Health Professional Schools: from an Opponent to an Ally. Medical Science Educator 2021;31(6):2209 View
  21. Hanenberg S, Mehlhorn N. Two N-of-1 self-trials on readability differences between anonymous inner classes (AICs) and lambda expressions (LEs) on Java code snippets. Empirical Software Engineering 2022;27(2) View
  22. Turki H, Hadj Taieb M, Shafee T, Lubiana T, Jemielniak D, Aouicha M, Labra Gayo J, Youngstrom E, Banat M, Das D, Mietchen D, on behalf of WikiProject COVID- , Haller A. Representing COVID-19 information in collaborative knowledge graphs: The case of Wikidata. Semantic Web 2022;13(2):233 View
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Books/Policy Documents

  1. Monlezun D. The Thinking Healthcare System. View
  2. Miller S, Moos W, Munk B, Munk S, Hart C, Spellmeyer D. Managing the Drug Discovery Process. View
  3. Lewoniewski W, Wȩcel K, Abramowicz W. Information Technology for Management: Approaches to Improving Business and Society. View