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KiS baner

Tom 67 Nr 1 (2023)

Z warsztatów badawczych

Development of Digital Culture Research — Bibliometric Analysis Using CiteSpace

DOI: https://doi.org/10.35757/KiS.2023.67.1.10
Przesłane: 25 sierpnia 2022
Opublikowane: 31 marca 2023

Abstrakt

The article contains a bibliometric analysis conducted on the basis of bibliographic data from the years 1996–2022, extracted from the Scopus database (May 2022). The method used involved steps beyond the traditional counting of publications and citations as well as drawing conclusions based on reading the content of academic papers. Complete biographic datasets were used for advanced analyses performed in the program CiteSpace. The state of research into digital culture may be described as follows: (1) it constitutes a new area of research that has seen particularly intensive development for the last 15 years or so; (2) systematic research is conducted by a small set of researchers; (3) they publish the findings of their research in a small selection of journals (around a dozen) and in books; (4) books contribute most to the development of such research (mainly around a dozen of the most popular ones); (5) the subject-matter of this research embraces mainly such issues as: copyright law, critical digital studies, digital art, network society, digital media, digital modernity, information technology, digitalisation, influencers, the internet era, memes, new media, social media, social networks, video games, and visual culture.

Bibliografia

  1. Berry David M., Fagerjord Anders, 2017, Digital Humanities, Polity Press, Cambridge.
  2. Bollmer Grant D., 2018, Theorizing Digital Cultures, Sage Publications, London.
  3. Chen Chaomei, Ibekwe-SanJuan Fidelia, Hou Jianhua, 2010, The Structure and Dynamics of Co-citation Clusters: A Multiple-perspective Co-citation Analysis, “Journal of the American Society for Information Science and Technology”, 61(7): 1386–1409.
  4. Chen Chaomei, 2020, How to Use CiteSpace, Lean Publishing.
  5. Chuquihuanca Yacsahuanca Nelson, Pesantes Shimajuko Soledad, Vásquez Rodriguez Luis, Vargas Elena, 2021, Cultura digital desde el contexto universitario en tiempos de pandemia Covid-19, “Revista Venezolana de Gerencia”, 26(95): 802–817.
  6. Deuze Marc, 2006, Participation, Remediation, Bricolage: Considering Principal Components of a Digital Culture, „The Information Society”, 22(2): 63–75.
  7. Fortunato Santo, Bergstrom Carl T., Börner Caty et al., 2018, Science of Science, “Science”, 359(6379) (https://www.science.org/doi/10.1126/science.aao0185).
  8. Gere Charlie, 2008, Digital Culture, Reaktion Books, London.
  9. Giannini Tula, Bowen Jonathan P., 2019, Museums and Digital Culture. New Perspectives and Research, Springer, Cham.
  10. Kleinberg Jon, 2002, Bursty and Hierarchical Structure in Streams. Paper presented at the Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Edmonton, Alberta, Canada (https://www.cs.cornell.edu/home/kleinber/bhs.pdf [accessed: 25.08.2022]).
  11. Koosel Stacey, 2011, Discourses in Digital Culture Research, “Kunstgeschichte. Open Peer Reviewed Journal” (https://www.kunstgeschichte-ejournal.net/172/ [accessed: 25.08.2022]).
  12. Kwiek Marek, 2015, Uniwersytet w dobie przemian [University in the age of change], Wydawnictwo Naukowe PWN, Warszawa.
  13. Manana-Rodriguez Jorge, 2015, A Critical Review of SCImago Journal & Country Rank, “Research Evaluation”, 24(4): 343–354.
  14. Miller Vincent, 2020, Understanding Digital Culture, Sage Publications, London.
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  17. Opaliński Łukasz, 2017b, Bibliometryczna metodologia prognozowania i oceny rozwoju dyscyplin naukowych. Analiza piśmiennictwa. Część 2. Badania porównawcze, hybrydowe, statystyczne, analizy dokumentów patentowych, ścieżek rozwoju dyscyplin oraz pozostałe oryginalne podejścia metodologiczne [Bibliometric Methods to Foresee and Assess the Development of Scientific Disciplines. Literature Analysis. Part 2. Comparisons, Hybrid and Statistical Methods, Analysis of Patents and Main Paths of Literature Development and Other Original Approaches in Terms of Predictive Methodology], “Zagadnienia Informacji Naukowej”, 55(2): 73–105.
  18. Prins Ad A.M., Costas Rodrigo, van Leeuwen Thed N., Wouters Paul F., 2016, Using Google Scholar in Research Evaluation of Humanities and Social Science Programs: A Comparison with Web of Science Data, “Research Evaluation”, 25(3): 264–270.
  19. Rousseeuw Peter J., 1987, Silhouettes: A Graphical Aid to the Interpretation and Validation of Cluster Analysis, “Journal of Computational and Applied Mathematics”, 20: 53–65.
  20. Small Henry, 1973, Co-citation in the Scientific Literature: A New Measure of the Relationship between Two Documents, “Journal of the American Society for Information Science”, 24(4): 265–269.
  21. Tabacaru Simona, 2019, Web of Science versus Scopus: Journal Coverage Overlap Analysis (https://oaktrust.library.tamu.edu/handle/1969.1/175137 [accessed: 25.08.2022]).
  22. Yuan Jing, Jianming Zheng, 2017, Study on Digital Culture Research by International Libraries since 2000, “Library Journal”, 36(6): 95–99.

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