IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v128y2023i5d10.1007_s11192-023-04686-6.html
   My bibliography  Save this article

The influence of discipline consistency between papers and published journals on citations: an analysis of Chinese papers in three social science disciplines

Author

Listed:
  • Kaile Gong

    (Nanjing Normal University)

Abstract

As research becomes more interdisciplinary, it is becoming more common for papers not to be published in their own disciplinary journals. This phenomenon is further amplified by the large number of multi-disciplinary journals in China’s social sciences, and prompts this study to explore the influence of discipline consistency between papers and published journals on citations. In this study, 476,327 Chinese papers in Economics, Law, and Library & Information Science published between 1998 and 2016 are collected from the Chinese Social Sciences Citation Index (CSSCI) as research samples. Descriptive statistics, Kruskal–Wallis test, Chi-square test, and regression analysis are used to compare the citation count and citation rate between papers published in own disciplinary journals, other disciplinary journals, and multi-disciplinary journals. It is found that papers whose discipline is consistent with published journals have a statistically significant citation advantage, which can be explained by the principle of least effort and scholars’ familiarity-based journal evaluation. According to the findings, this study also discusses some issues on the development of multi-disciplinary journals and the usage of citation indicators in academic evaluation.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:128:y:2023:i:5:d:10.1007_s11192-023-04686-6
    DOI: 10.1007/s11192-023-04686-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-023-04686-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-023-04686-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jeppe Nicolaisen & Tove Faber Frandsen, 2019. "Zero impact: a large-scale study of uncitedness," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1227-1254, May.
    2. Juan Xie & Kaile Gong & Ying Cheng & Qing Ke, 2019. "The correlation between paper length and citations: a meta-analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 763-786, March.
    3. Benjamin M. Althouse & Jevin D. West & Carl T. Bergstrom & Theodore Bergstrom, 2009. "Differences in impact factor across fields and over time," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(1), pages 27-34, January.
    4. Serenko, Alexander & Bontis, Nick, 2011. "What's familiar is excellent: The impact of exposure effect on perceived journal quality," Journal of Informetrics, Elsevier, vol. 5(1), pages 219-223.
    5. Per Ahlgren & Cristian Colliander & Peter Sjögårde, 2018. "Exploring the relation between referencing practices and citation impact: A large†scale study based on Web of Science data," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(5), pages 728-743, May.
    6. Hongyu Zhou & Raf Guns & Tim C. E. Engels, 2022. "Are social sciences becoming more interdisciplinary? Evidence from publications 1960–2014," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(9), pages 1201-1221, September.
    7. Yanhui Song & Feng Ma & Siluo Yang, 2015. "Comparative study on the obsolescence of humanities and social sciences in China: under the new situation of web," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 365-388, January.
    8. Jeff Tollefson, 2018. "China declared world’s largest producer of scientific articles," Nature, Nature, vol. 553(7689), pages 390-390, January.
    9. Erjia Yan & Chaojiang Wu & Min Song, 2018. "The funding factor: a cross-disciplinary examination of the association between research funding and citation impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 369-384, April.
    10. 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.
    11. 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.
    12. Stremersch, Stefan & Camacho, Nuno & Vanneste, Sofie & Verniers, Isabel, 2015. "Unraveling scientific impact: Citation types in marketing journals," International Journal of Research in Marketing, Elsevier, vol. 32(1), pages 64-77.
    13. Kun Chen & Xian-tong Ren & Guo-liang Yang & Hai-bo Qin, 2022. "The other side of the coin: The declining of Chinese social science," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 127-143, January.
    14. Kaile Gong & Ying Cheng, 2022. "Patterns and impact of collaboration in China’s social sciences: cross-database comparisons between CSSCI and SSCI," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5947-5964, October.
    15. 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.
    16. Thelwall, Mike & Wilson, Paul, 2014. "Regression for citation data: An evaluation of different methods," Journal of Informetrics, Elsevier, vol. 8(4), pages 963-971.
    17. Fei Shu & Yue Ma & Junping Qiu & Vincent Larivière, 2020. "Classifications of science and their effects on bibliometric evaluations," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2727-2744, December.
    18. Alexander Serenko & Nick Bontis, 2018. "A critical evaluation of expert survey†based journal rankings: The role of personal research interests," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(5), pages 749-752, May.
    19. Juan Xie & Kaile Gong & Jiang Li & Qing Ke & Hyonchol Kang & Ying Cheng, 2019. "A probe into 66 factors which are possibly associated with the number of citations an article received," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1429-1454, June.
    20. Guido Pepermans & Sandra Rousseau, 2016. "The decision to submit to a journal: Another example of a valence-consistent Shift?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(6), pages 1372-1383, June.
    21. Iman Tahamtan & Askar Safipour Afshar & Khadijeh Ahamdzadeh, 2016. "Factors affecting number of citations: a comprehensive review of the literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1195-1225, June.
    22. Bornmann, Lutz & Schier, Hermann & Marx, Werner & Daniel, Hans-Dieter, 2012. "What factors determine citation counts of publications in chemistry besides their quality?," Journal of Informetrics, Elsevier, vol. 6(1), pages 11-18.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Martorell Cunil, Onofre & Otero González, Luis & Durán Santomil, Pablo & Mulet Forteza, Carlos, 2023. "How to accomplish a highly cited paper in the tourism, leisure and hospitality field," Journal of Business Research, Elsevier, vol. 157(C).
    2. Liu, Jialin & Chen, Hongkan & Liu, Zhibo & Bu, Yi & Gu, Weiye, 2022. "Non-linearity between referencing behavior and citation impact: A large-scale, discipline-level analysis," Journal of Informetrics, Elsevier, vol. 16(3).
    3. 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.
    4. Zahedi, Zohreh & Haustein, Stefanie, 2018. "On the relationships between bibliographic characteristics of scientific documents and citation and Mendeley readership counts: A large-scale analysis of Web of Science publications," Journal of Informetrics, Elsevier, vol. 12(1), pages 191-202.
    5. Kaile Gong & Ying Cheng, 2022. "Patterns and impact of collaboration in China’s social sciences: cross-database comparisons between CSSCI and SSCI," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5947-5964, October.
    6. Peter Sjögårde & Fereshteh Didegah, 2022. "The association between topic growth and citation impact of research publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1903-1921, April.
    7. Mingyang Wang & Zhenyu Wang & Guangsheng Chen, 2019. "Which can better predict the future success of articles? Bibliometric indices or alternative metrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1575-1595, June.
    8. Tahamtan, Iman & Bornmann, Lutz, 2018. "Core elements in the process of citing publications: Conceptual overview of the literature," Journal of Informetrics, Elsevier, vol. 12(1), pages 203-216.
    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).
    10. Copiello, Sergio, 2019. "Peer and neighborhood effects: Citation analysis using a spatial autoregressive model and pseudo-spatial data," Journal of Informetrics, Elsevier, vol. 13(1), pages 238-254.
    11. Zhang, Xinyuan & Xie, Qing & Song, Min, 2021. "Measuring the impact of novelty, bibliometric, and academic-network factors on citation count using a neural network," Journal of Informetrics, Elsevier, vol. 15(2).
    12. Melika Mosleh & Saeed Roshani & Mario Coccia, 2022. "Scientific laws of research funding to support citations and diffusion of knowledge in life science," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1931-1951, April.
    13. Sepideh Fahimifar & Khadijeh Mousavi & Fatemeh Mozaffari & Marcel Ausloos, 2023. "Identification of the most important external features of highly cited scholarly papers through 3 (i.e., Ridge, Lasso, and Boruta) feature selection data mining methods," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3685-3712, August.
    14. Hongquan Shen & Juan Xie & Jiang Li & Ying Cheng, 2021. "The correlation between scientific collaboration and citation count at the paper level: a meta-analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3443-3470, April.
    15. Yifan Qian & Wenge Rong & Nan Jiang & Jie Tang & Zhang Xiong, 2017. "Citation regression analysis of computer science publications in different ranking categories and subfields," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1351-1374, March.
    16. Ha, Taehyun, 2022. "An explainable artificial-intelligence-based approach to investigating factors that influence the citation of papers," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    17. Ajiferuke, Isola & Famoye, Felix, 2015. "Modelling count response variables in informetric studies: Comparison among count, linear, and lognormal regression models," Journal of Informetrics, Elsevier, vol. 9(3), pages 499-513.
    18. 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.
    19. Shanwu Tian & Xiurui Xu & Ping Li, 2021. "Acknowledgement network and citation count: the moderating role of collaboration network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7837-7857, September.
    20. Chunli Wei & Jingyi Zhao & Jue Ni & Jiang Li, 2023. "What does open peer review bring to scientific articles? Evidence from PLoS journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2763-2776, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:128:y:2023:i:5:d:10.1007_s11192-023-04686-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.