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Optimizing SCImago Journal & Country Rank classification by community detection

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  • Gómez-Núñez, Antonio J.
  • Batagelj, Vladimir
  • Vargas-Quesada, Benjamín
  • Moya-Anegón, Félix
  • Chinchilla-Rodríguez, Zaida

Abstract

Subject classification arises as an important topic for bibliometrics and scientometrics, searching to develop reliable and consistent tools and outputs. Such objectives also call for a well delimited underlying subject classification scheme that adequately reflects scientific fields. Within the broad ensemble of classification techniques, clustering analysis is one of the most successful.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:infome:v:8:y:2014:i:2:p:369-383
    DOI: 10.1016/j.joi.2014.01.011
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    Cited by:

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    2. Jing Zhang & Xiaomin Liu & Lili Wu, 2016. "The study of subject-classification based on journal coupling and expert subject-classification system," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1149-1170, June.
    3. 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.
    4. 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.
    5. Muñoz-Écija, Teresa & Vargas-Quesada, Benjamín & Chinchilla Rodríguez, Zaida, 2019. "Coping with methods for delineating emerging fields: Nanoscience and nanotechnology as a case study," Journal of Informetrics, Elsevier, vol. 13(4).
    6. Leydesdorff, Loet & Bornmann, Lutz & Zhou, Ping, 2016. "Construction of a pragmatic base line for journal classifications and maps based on aggregated journal-journal citation relations," Journal of Informetrics, Elsevier, vol. 10(4), pages 902-918.
    7. Liwei Cai & Jiahao Tian & Jiaying Liu & Xiaomei Bai & Ivan Lee & Xiangjie Kong & Feng Xia, 2019. "Scholarly impact assessment: a survey of citation weighting solutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 453-478, February.
    8. 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.

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