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Impact of Article Language in Multi-Language Medical Journals - a Bibliometric Analysis of Self-Citations and Impact Factor

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  • Torsten Diekhoff
  • Peter Schlattmann
  • Marc Dewey

Abstract

Background: In times of globalization there is an increasing use of English in the medical literature. The aim of this study was to analyze the influence of English-language articles in multi-language medical journals on their international recognition – as measured by a lower rate of self-citations and higher impact factor (IF). Methods and Findings: We analyzed publications in multi-language journals in 2008 and 2009 using the Web of Science (WoS) of Thomson Reuters (former Institute of Scientific Information) and PubMed as sources of information. The proportion of English-language articles during the period was compared with both the share of self-citations in the year 2010 and the IF with and without self-citations. Multivariable linear regression analysis was performed to analyze these factors as well as the influence of the journals‘ countries of origin and of the other language(s) used in publications besides English. Conclusion: Our findings suggest that a larger share of English articles in multi-language medical journals is associated with greater international recognition. Fewer self-citations were found in multi-language journals with a greater share of original articles in English.

Suggested Citation

  • Torsten Diekhoff & Peter Schlattmann & Marc Dewey, 2013. "Impact of Article Language in Multi-Language Medical Journals - a Bibliometric Analysis of Self-Citations and Impact Factor," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-1, October.
    • Handle: RePEc:plo:pone00:0076816
    DOI: 10.1371/journal.pone.0076816
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    References listed on IDEAS

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    1. Youliang Huang & Mingquan Zhou & Qingqiong Deng & Juan Zhang & Pengbo Zhou & XianGang Shang, 2015. "Bibliometric analysis for the literature of traditional Chinese medicine in PubMed," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 557-566, October.
    2. 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.
    3. Khosrowjerdi, Mahmood & Bornmann, Lutz, 2021. "Is culture related to strong science? An empirical investigation," Journal of Informetrics, Elsevier, vol. 15(4).
    4. Jamali, Seyedh Mahboobeh & Md Zain, Ahmad Nurulazam & Samsudin, Mohd Ali & Ale Ebrahim, Nader, 2015. "Publication Trends in Physics Education: A Bibliometric study," MPRA Paper 79524, University Library of Munich, Germany, revised 2015.
    5. Dehdarirad, Tahereh & Nasini, Stefano, 2017. "Research impact in co-authorship networks: a two-mode analysis," Journal of Informetrics, Elsevier, vol. 11(2), pages 371-388.
    6. Adilson Marcos Montefusco & Felipe Parra Nascimento & Luiz Ubirajara Sennes & Ricardo Ferreira Bento & Rui Imamura, 2019. "Influence of international authorship on citations in Brazilian medical journals: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1487-1496, June.
    7. Chang, Yu-Wei, 2022. "Capability of non-English-speaking countries for securing a foothold in international journal publishing," Journal of Informetrics, Elsevier, vol. 16(3).
    8. Václav Linkov & Kieran O’Doherty & Eunsoo Choi & Gyuseog Han, 2021. "Linguistic Diversity Index: A Scientometric Measure to Enhance the Relevance of Small and Minority Group Languages," SAGE Open, , vol. 11(2), pages 21582440211, April.
    9. 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).

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