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The design and application value of the Chinese Social Science Citation Index

Author

Listed:
  • Xinning Su

    (Nanjing University)

  • Sanhong Deng

    (Nanjing University)

  • Si Shen

    (Nanjing University)

Abstract

From the application point of view, this article introduces the framework of the Chinese Social Science Citation Index (CSSCI). It expounds the idea of designing the CSSCI system, and its major functions and features in particular. The data organization as well as data encoding methods of the CSSCI system is well explained. Moreover, this article elaborates on how the citation index data can be used in analyzing discipline features, exploring research hotspots and developing trends, identifying important academic works and constructing academic network. Such efforts are supposed to help the readers better understand the application value of citation index system. It also provides the academic circle with a new understanding of citation index system.

Suggested Citation

  • Xinning Su & Sanhong Deng & Si Shen, 2014. "The design and application value of the Chinese Social Science Citation Index," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1567-1582, March.
    • Handle: RePEc:spr:scient:v:98:y:2014:i:3:d:10.1007_s11192-012-0921-4
    DOI: 10.1007/s11192-012-0921-4
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    References listed on IDEAS

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    5. A. V. Chumachenko & B. G. Kreminskyi & Iu. L. Mosenkis & A. I. Yakimenko, 2020. "Dynamics of topic formation and quantitative analysis of hot trends in physical science," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 739-753, October.
    6. Kaile Gong, 2023. "The influence of discipline consistency between papers and published journals on citations: an analysis of Chinese papers in three social science disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 3129-3146, May.
    7. Kaile Gong & Juan Xie & Ying Cheng & Vincent Larivière & Cassidy R. Sugimoto, 2019. "The citation advantage of foreign language references for Chinese social science papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1439-1460, September.
    8. Jiang Li & Yueting Li, 2015. "Patterns and evolution of coauthorship in China’s humanities and social sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 1997-2010, March.
    9. Ruan, Xuanmin & Zhu, Yuanyang & Li, Jiang & Cheng, Ying, 2020. "Predicting the citation counts of individual papers via a BP neural network," Journal of Informetrics, Elsevier, vol. 14(3).
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    11. Xin Li & Qiang Yao & Xuli Tang & Qian Li & Mengjia Wu, 2020. "How to investigate the historical roots and evolution of research fields in China? A case study on iMetrics using RootCite," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1253-1274, November.
    12. Zhang, Baolong & Wang, Hao & Deng, Sanhong & Su, Xinning, 2020. "Measurement and analysis of Chinese journal discriminative capacity," Journal of Informetrics, Elsevier, vol. 14(1).
    13. Olga Moskaleva & Vladimir Pislyakov & Ivan Sterligov & Mark Akoev & Svetlana Shabanova, 2018. "Russian Index of Science Citation: Overview and review," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 449-462, July.
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