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Journal cross-citation analysis for validation and improvement of journal-based subject classification in bibliometric research

Author

Listed:
  • Lin Zhang

    (K. U. Leuven
    WISE Lab, Dalian University of Technology)

  • Frizo Janssens

    (K. U. Leuven
    K. U. Leuven, ESAT-SCD)

  • Liming Liang

    (WISE Lab, Dalian University of Technology
    Institute for Science, Technology, and Society, Henan Normal University)

  • Wolfgang Glänzel

    (K. U. Leuven
    Hungarian Academy of Sciences, IRPS)

Abstract

The objective of this study is to use a clustering algorithm based on journal cross-citation to validate and to improve the journal-based subject classification schemes. The cognitive structure based on the clustering is visualized by the journal cross-citation network and three kinds of representative journals in each cluster among the communication network have been detected and analyzed. As an existing reference system the 15-field subject classification by Glänzel and Schubert (Scientometrics 56:55–73, 2003) has been compared with the clustering structure.

Suggested Citation

  • Lin Zhang & Frizo Janssens & Liming Liang & Wolfgang Glänzel, 2010. "Journal cross-citation analysis for validation and improvement of journal-based subject classification in bibliometric research," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(3), pages 687-706, March.
    • Handle: RePEc:spr:scient:v:82:y:2010:i:3:d:10.1007_s11192-010-0180-1
    DOI: 10.1007/s11192-010-0180-1
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    References listed on IDEAS

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    8. Wolfgang Glänzel & András Schubert, 2003. "A new classification scheme of science fields and subfields designed for scientometric evaluation purposes," Scientometrics, Springer;Akadémiai Kiadó, vol. 56(3), pages 357-367, March.
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    12. Loet Leydesdorff, 2004. "Top-down decomposition of the Journal Citation Reportof the Social Science Citation Index: Graph- and factor-analytical approaches," Scientometrics, Springer;Akadémiai Kiadó, vol. 60(2), pages 159-180, June.
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    Cited by:

    1. Bart Thijs & Lin Zhang & Wolfgang Glänzel, 2015. "Bibliographic coupling and hierarchical clustering for the validation and improvement of subject-classification schemes," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1453-1467, December.
    2. Wang, Qi & Waltman, Ludo, 2016. "Large-scale analysis of the accuracy of the journal classification systems of Web of Science and Scopus," Journal of Informetrics, Elsevier, vol. 10(2), pages 347-364.
    3. Manuel Goyanes & Márton Demeter & Aurea Grané & Irene Albarrán-Lozano & Homero Gil de Zúñiga, 2020. "A mathematical approach to assess research diversity: operationalization and applicability in communication sciences, political science, and beyond," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2299-2322, December.
    4. Yuen-Hsien Tseng & Ming-Yueh Tsay, 2013. "Journal clustering of library and information science for subfield delineation using the bibliometric analysis toolkit: CATAR," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 503-528, May.
    5. Juste Raimbault, 2019. "Exploration of an interdisciplinary scientific landscape," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 617-641, May.
    6. Yu-Wei Chang, 2019. "Are articles in library and information science (LIS) journals primarily contributed to by LIS authors?," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 81-104, October.
    7. Yang, Siluo & Wang, Feifei, 2015. "Visualizing information science: Author direct citation analysis in China and around the world," Journal of Informetrics, Elsevier, vol. 9(1), pages 208-225.
    8. Lin Zhang & Beibei Sun & Fei Shu & Ying Huang, 2022. "Comparing paper level classifications across different methods and systems: an investigation of Nature publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7633-7651, December.
    9. Cristóbal Urbano & Jordi Ardanuy, 2020. "Cross-disciplinary collaboration versus coexistence in LIS serials: analysis of authorship affiliations in four European countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 575-602, July.
    10. Janghyeok Yoon & Sungchul Choi & Kwangsoo Kim, 2011. "Invention property-function network analysis of patents: a case of silicon-based thin film solar cells," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(3), pages 687-703, March.
    11. Werner Marx & Lutz Bornmann, 2016. "Change of perspective: bibliometrics from the point of view of cited references—a literature overview on approaches to the evaluation of cited references in bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1397-1415, November.
    12. Kim, Hyeyoung & Park, Hyelin & Song, Min, 2022. "Developing a topic-driven method for interdisciplinarity analysis," Journal of Informetrics, Elsevier, vol. 16(2).
    13. Shu, Fei & Julien, Charles-Antoine & Zhang, Lin & Qiu, Junping & Zhang, Jing & Larivière, Vincent, 2019. "Comparing journal and paper level classifications of science," Journal of Informetrics, Elsevier, vol. 13(1), pages 202-225.
    14. Gómez-Núñez, Antonio J. & Batagelj, Vladimir & Vargas-Quesada, Benjamín & Moya-Anegón, Félix & Chinchilla-Rodríguez, Zaida, 2014. "Optimizing SCImago Journal & Country Rank classification by community detection," Journal of Informetrics, Elsevier, vol. 8(2), pages 369-383.
    15. Yang, Siluo & Han, Ruizhen & Wolfram, Dietmar & Zhao, Yuehua, 2016. "Visualizing the intellectual structure of information science (2006–2015): Introducing author keyword coupling analysis," Journal of Informetrics, Elsevier, vol. 10(1), pages 132-150.

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