IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0228713.html
   My bibliography  Save this article

Science through Wikipedia: A novel representation of open knowledge through co-citation networks

Author

Listed:
  • Wenceslao Arroyo-Machado
  • Daniel Torres-Salinas
  • Enrique Herrera-Viedma
  • Esteban Romero-Frías

Abstract

This study provides an overview of science from the Wikipedia perspective. A methodology has been established for the analysis of how Wikipedia editors regard science through their references to scientific papers. The method of co-citation has been adapted to this context in order to generate Pathfinder networks (PFNET) that highlight the most relevant scientific journals and categories, and their interactions in order to find out how scientific literature is consumed through this open encyclopaedia. In addition to this, their obsolescence has been studied through Price index. A total of 1 433 457 references available at Altmetric.com have been initially taken into account. After pre-processing and linking them to the data from Elsevier's CiteScore Metrics the sample was reduced to 847 512 references made by 193 802 Wikipedia articles to 598 746 scientific articles belonging to 14 149 journals indexed in Scopus. As highlighted results we found a significative presence of “Medicine” and “Biochemistry, Genetics and Molecular Biology” papers and that the most important journals are multidisciplinary in nature, suggesting also that high-impact factor journals were more likely to be cited. Furthermore, only 13.44% of Wikipedia citations are to Open Access journals.

Suggested Citation

  • Wenceslao Arroyo-Machado & Daniel Torres-Salinas & Enrique Herrera-Viedma & Esteban Romero-Frías, 2020. "Science through Wikipedia: A novel representation of open knowledge through co-citation networks," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-20, February.
  • Handle: RePEc:plo:pone00:0228713
    DOI: 10.1371/journal.pone.0228713
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0228713
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0228713&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0228713?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Antonio Eleazar Serrano-López & Peter Ingwersen & Elias Sanz-Casado, 2017. "Wind power research in Wikipedia: Does Wikipedia demonstrate direct influence of research publications and can it be used as adequate source in research evaluation?," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1471-1488, September.
    2. Loet Leydesdorff & Adina Nerghes, 2017. "Co-word maps and topic modeling: A comparison using small and medium-sized corpora (N > 1,000)," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 1024-1035, April.
    3. Silva, Filipi N. & Amancio, Diego R. & Bardosova, Maria & Costa, Luciano da F. & Oliveira, Osvaldo N., 2016. "Using network science and text analytics to produce surveys in a scientific topic," Journal of Informetrics, Elsevier, vol. 10(2), pages 487-502.
    4. Misha Teplitskiy & Grace Lu & Eamon Duede, 2017. "Amplifying the impact of open access: Wikipedia and the diffusion of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(9), pages 2116-2127, September.
    5. Alesia Zuccala, 2006. "Author Cocitation Analysis is to intellectual structure as Web Colink Analysis is to …?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(11), pages 1487-1502, September.
    6. Félix Moya-Anegón & Benjamín Vargas-Quesada & Victor Herrero-Solana & Zaida Chinchilla-Rodríguez & Elena Corera-Álvarez & Francisco J. Munoz-Fernández, 2004. "A new technique for building maps of large scientific domains based on the cocitation of classes and categories," Scientometrics, Springer;Akadémiai Kiadó, vol. 61(1), pages 129-145, September.
    7. Loet Leydesdorff & Ismael Rafols, 2009. "A global map of science based on the ISI subject categories," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(2), pages 348-362, February.
    8. Don Fallis, 2008. "Toward an epistemology of Wikipedia," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(10), pages 1662-1674, August.
    9. Lutz Bornmann & Robin Haunschild, 2016. "Overlay maps based on Mendeley data: The use of altmetrics for readership networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(12), pages 3064-3072, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Torres-Salinas, Daniel & Romero-Frías, Esteban & Arroyo-Machado, Wenceslao, 2019. "Mapping the backbone of the Humanities through the eyes of Wikipedia," Journal of Informetrics, Elsevier, vol. 13(3), pages 793-803.
    2. Ying Huang & Wolfgang Glänzel & Lin Zhang, 2021. "Tracing the development of mapping knowledge domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6201-6224, July.
    3. Jielan Ding & Per Ahlgren & Liying Yang & Ting Yue, 2018. "Disciplinary structures in Nature, Science and PNAS: journal and country levels," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1817-1852, September.
    4. Carusi, Chiara & Bianchi, Giuseppe, 2019. "Scientific community detection via bipartite scholar/journal graph co-clustering," Journal of Informetrics, Elsevier, vol. 13(1), pages 354-386.
    5. Loet Leydesdorff & Lutz Bornmann, 2012. "Mapping (USPTO) patent data using overlays to Google Maps," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(7), pages 1442-1458, July.
    6. Miguel R. Guevara & Dominik Hartmann & Manuel Aristarán & Marcelo Mendoza & César A. Hidalgo, 2016. "The research space: using career paths to predict the evolution of the research output of individuals, institutions, and nations," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1695-1709, December.
    7. Ricardo Arencibia-Jorge & Rosa Lidia Vega-Almeida & José Luis Jiménez-Andrade & Humberto Carrillo-Calvet, 2022. "Evolutionary stages and multidisciplinary nature of artificial intelligence research," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5139-5158, September.
    8. Ismael Rafols & Martin Meyer, 2010. "Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 263-287, February.
    9. Ismael Rafols & Alan Porter & Loet Leydesdorff, 2009. "Overlay Maps of Science: a New Tool for Research Policy," SPRU Working Paper Series 179, SPRU - Science Policy Research Unit, University of Sussex Business School.
    10. Yan, Erjia & Ding, Ying & Cronin, Blaise & Leydesdorff, Loet, 2013. "A bird's-eye view of scientific trading: Dependency relations among fields of science," Journal of Informetrics, Elsevier, vol. 7(2), pages 249-264.
    11. Andrea Bonaccorsi & Nicola Melluso & Francesco Alessandro Massucci, 2022. "Exploring the antecedents of interdisciplinarity at the European Research Council: a topic modeling approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 6961-6991, December.
    12. Shunshun Shi & Wenyu Zhang & Shuai Zhang & Jie Chen, 2018. "Does prestige dimension influence the interdisciplinary performance of scientific entities in knowledge flow? Evidence from the e-government field," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 1237-1264, November.
    13. Rongying Zhao & Bikun Chen, 2014. "Applying author co-citation analysis to user interaction analysis: a case study on instant messaging groups," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 985-997, November.
    14. Karmen Stopar & Damjana Drobne & Klemen Eler & Tomaz Bartol, 2016. "Citation analysis and mapping of nanoscience and nanotechnology: identifying the scope and interdisciplinarity of research," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 563-581, February.
    15. Quirin, Arnaud & Cordón, Oscar & Vargas-Quesada, Benjamín & de Moya-Anegón, Félix, 2010. "Graph-based data mining: A new tool for the analysis and comparison of scientific domains represented as scientograms," Journal of Informetrics, Elsevier, vol. 4(3), pages 291-312.
    16. Seokbeom Kwon & Alan Porter & Jan Youtie, 2016. "Navigating the innovation trajectories of technology by combining specialization score analyses for publications and patents: graphene and nano-enabled drug delivery," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 1057-1071, March.
    17. Zhang, Lin & Liu, Xinhai & Janssens, Frizo & Liang, Liming & Glänzel, Wolfgang, 2010. "Subject clustering analysis based on ISI category classification," Journal of Informetrics, Elsevier, vol. 4(2), pages 185-193.
    18. Kose, Toshihiro & Sakata, Ichiro, 2019. "Identifying technology convergence in the field of robotics research," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 751-766.
    19. Andrea Bonaccorsi & Filippo Chiarello & Gualtiero Fantoni, 2021. "Impact for whom? Mapping the users of public research with lexicon-based text mining," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1745-1774, February.
    20. Stephen Carley & Alan L. Porter, 2012. "A forward diversity index," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 407-427, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0228713. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.