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Author Credit for Transdisciplinary Collaboration

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  • Jian Xu
  • Ying Ding
  • Vincent Malic

Abstract

Transdisciplinary collaboration is the key for innovation. An evaluation mechanism is necessary to ensure that academic credit for this costly process can be allocated fairly among coauthors. This paper proposes a set of quantitative measures (e.g., t_credit and t_index) to reflect authors’ transdisciplinary contributions to publications. These measures are based on paper-topic probability distributions and author-topic probability distributions. We conduct an empirical analysis of the information retrieval domain which demonstrates that these measures effectively improve the results of harmonic_credit and h_index measures by taking into account the transdisciplinary contributions of authors. The definitions of t_credit and t_index provide a fair and effective way for research organizations to assign credit to authors of transdisciplinary publications.

Suggested Citation

  • Jian Xu & Ying Ding & Vincent Malic, 2015. "Author Credit for Transdisciplinary Collaboration," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-19, September.
    • Handle: RePEc:plo:pone00:0137968
    DOI: 10.1371/journal.pone.0137968
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    Cited by:

    1. Jian Xu & Yi Bu & Ying Ding & Sinan Yang & Hongli Zhang & Chen Yu & Lin Sun, 2018. "Understanding the formation of interdisciplinary research from the perspective of keyword evolution: a case study on joint attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 973-995, November.
    2. Baitong Chen & Ying Ding & Feicheng Ma, 2018. "Semantic word shifts in a scientific domain," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 211-226, October.
    3. Frode Eika Sandnes, 2021. "A bibliometric study of human–computer interaction research activity in the Nordic-Baltic Eight countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4733-4767, June.
    4. Li, Xin & Tang, Xuli, 2021. "Characterizing interdisciplinarity in drug research: A translational science perspective," Journal of Informetrics, Elsevier, vol. 15(4).
    5. Evelyn Eika & Frode Eika Sandnes, 2022. "Starstruck by journal prestige and citation counts? On students’ bias and perceptions of trustworthiness according to clues in publication references," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6363-6390, November.

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