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Scientometrics

, Volume 117, Issue 1, pp 271–291 | Cite as

Interdisciplinarity and collaboration: on the relationship between disciplinary diversity in departmental affiliations and reference lists

  • Lin Zhang
  • Beibei Sun
  • Zaida Chinchilla-Rodríguez
  • Lixin Chen
  • Ying Huang
Article

Abstract

This study explores the characteristics of scientific activity patterns through co-author affiliations to obtain new insights into interdisciplinary research. To classify the interdisciplinarity in research, we explored and compared two different approaches: the diversity of disciplines reflected in the listed affiliations of the authors and the diversity of the subject categories reflected in the reference list. To assess the diversity in departmental affiliations, we developed an explorative methodology that retrieves feature words from a combination of manual work and the thesaurus function in the Thomson Data Analyzer text mining tool. To assess the diversity in references, we followed the conventional approach applied in previous work. With both approaches, we relied on diversity as the measure for assessing interdisciplinarity of 157,710 articles published in PloS One (2007–2016). Based on a comparison between the results of both approaches, our study confirms that different methodologies and indicators can produce seriously inconsistent, and even contradictory results. In addition, different indicators may capture different understandings of such a multi-faceted concept as interdisciplinarity. Our results are summarized in a schematic representation of this twofold perspective as a method of indexing the different types of interdisciplinarity commonly found in research studies.

Keywords

Collaborations Affiliations Reference analysis Diversity Interdisciplinarity Interdisciplinary research PloS One 

Notes

Acknowledgements

The present study is an extended version of an article presented at the 16th International Conference on Scientometrics and Informetrics, Wuhan (China), 16–20 October 2017 (Zhang et al. 2017). The authors would like to acknowledge support from the National Natural Science Foundation of China (Grant No. 71573085), the Innovation Talents of Science and Technology in HeNan Province (Grant Nos. 16HASTIT038, 2015GGJS-108), and the Excellent Scholarship in Social Science in HeNan Province (No. 2018-YXXZ-10). We thank Giovanni Abramo and Ronald Rousseau for inspiring discussions.

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Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2018

Authors and Affiliations

  1. 1.School of Information ManagementWuhan UniversityWuhanChina
  2. 2.Department MSI, Centre for R&D Monitoring (ECOOM)KU LeuvenLeuvenBelgium
  3. 3.Department of Management and EconomicsNorth China University of Water Resources and Electric PowerZhengzhouChina
  4. 4.Institute of Policies and Public GoodsSpanish National Research Council (CSIC-IPP)MadridSpain
  5. 5.Department of Public AdministrationHunan UniversityChangshaChina

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