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Health warning: might contain multiple personalities—the problem of homonyms in Thomson Reuters Essential Science Indicators

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  • Anne-Wil Harzing

    (Middlesex University)

Abstract

Author name ambiguity is a crucial problem in any type of bibliometric analysis. It arises when several authors share the same name, but also when one author expresses their name in different ways. This article focuses on the former, also called the “namesake” problem. In particular, we assess the extent to which this compromises the Thomson Reuters Essential Science Indicators ranking of the top 1 % most cited authors worldwide. We show that three demographic characteristics that should be unrelated to research productivity—name origin, uniqueness of one’s family name, and the number of initials used in publishing—in fact have a very strong influence on it. In contrast to what could be expected from Web of Science publication data, researchers with Asian names—and in particular Chinese and Korean names—appear to be far more productive than researchers with Western names. Furthermore, for any country, academics with common names and fewer initials also appear to be more productive than their more uniquely named counterparts. However, this appearance of high productivity is caused purely by the fact that these “academic superstars” are in fact composites of many individual academics with the same name. We thus argue that it is high time that Thomson Reuters starts taking name disambiguation in general and non-Anglophone names in particular more seriously.

Suggested Citation

  • Anne-Wil Harzing, 2015. "Health warning: might contain multiple personalities—the problem of homonyms in Thomson Reuters Essential Science Indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2259-2270, December.
  • Handle: RePEc:spr:scient:v:105:y:2015:i:3:d:10.1007_s11192-015-1699-y
    DOI: 10.1007/s11192-015-1699-y
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    References listed on IDEAS

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    1. Anne-Wil Harzing, 2013. "A preliminary test of Google Scholar as a source for citation data: a longitudinal study of Nobel prize winners," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1057-1075, March.
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    3. Jia Zhu & Yi Yang & Qing Xie & Liwei Wang & Saeed-Ul Hassan, 2014. "Robust hybrid name disambiguation framework for large databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 2255-2274, March.
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    5. Andreas Strotmann & Dangzhi Zhao, 2012. "Author name disambiguation: What difference does it make in author-based citation analysis?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(9), pages 1820-1833, September.
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    7. Anne-Wil Harzing, 2013. "Document categories in the ISI Web of Knowledge: Misunderstanding the Social Sciences?," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 23-34, January.
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