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Tracing the role of individual journals in a cross-citation network based on different indicators

Author

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  • Lin Zhang

    (Dalian University of Technology
    K.U. Leuven, Centre for R&D Monitoring)

  • Wolfgang Glänzel

    (K.U. Leuven, Centre for R&D Monitoring
    IRPS)

  • Liming Liang

    (Dalian University of Technology
    Henan Normal University)

Abstract

This study aims at detecting the role of individual journals and uncovering structural patterns of information flow among scientific journals in a cross-citation network, using different bibliometric indicators and statistical methods of data analysis. Beyond measuring the individual journals’ position within the communication network, we shed light on their cognitive background as well. Language barrier and lacking internationality proved one of the main hindrances for integration into the communication network. Moreover, some document types hinder journals from establishing self-links. Against our expectations, we have found a clear divergence between strongly interlinked and high-entropy journals. Furthermore, the analysis of strong links among different fields allows the detection of high-interdisciplinary journals.

Suggested Citation

  • Lin Zhang & Wolfgang Glänzel & Liming Liang, 2009. "Tracing the role of individual journals in a cross-citation network based on different indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 821-838, December.
    • Handle: RePEc:spr:scient:v:81:y:2009:i:3:d:10.1007_s11192-008-2245-y
    DOI: 10.1007/s11192-008-2245-y
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. 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.
    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. Wolfgang Glänzel, 2012. "The role of core documents in bibliometric network analysis and their relation with h-type indices," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(1), pages 113-123, October.
    5. Wolfgang Glänzel & Bart Thijs, 2011. "Using ‘core documents’ for the representation of clusters and topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 297-309, July.
    6. A. Abrizah & A. Noorhidawati & A. N. Zainab, 2015. "LIS journals categorization in the Journal Citation Report: a stated preference study," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1083-1099, February.
    7. Matthew A. Shapiro, 2012. "Receiving information at Korean and Taiwanese universities, industry, and GRIs," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(1), pages 289-309, January.
    8. Andrea Mervar & Maja Jokić, 2022. "Core-periphery nexus in the EU social sciences: bibliometric perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5793-5817, October.
    9. Ephrance Abu Ujum & Sameer Kumar & Kuru Ratnavelu & Gangan Prathap, 2021. "A new journal power-weakness ratio to measure journal impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9051-9068, November.
    10. Wolfgang Glänzel & Bart Thijs, 2012. "Using ‘core documents’ for detecting and labelling new emerging topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 399-416, May.
    11. Wang, Feifei & Dong, Jiaxin & Lu, Wanzhao & Xu, Shuo, 2023. "Collaboration prediction based on multilayer all-author tripartite citation networks: A case study of gene editing," Journal of Informetrics, Elsevier, vol. 17(1).
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    13. Wang, Feifei & Jia, Chenran & Wang, Xiaohan & Liu, Junwan & Xu, Shuo & Liu, Yang & Yang, Chenyuyan, 2019. "Exploring all-author tripartite citation networks: A case study of gene editing," Journal of Informetrics, Elsevier, vol. 13(3), pages 856-873.
    14. András Schubert, 2010. "A reference-based Hirschian similarity measure for journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(1), pages 133-147, July.

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