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

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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.

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Notes

  1. For example, at the level of consolidated scientific research programmes, US science and technology funding agencies are increasingly supporting large-scale, centralized, grant-based research projects that span multiple disciplines and institutions (Corley et al. 2006). European programs are promoting collaboration and creating regional and international scientific networks of different generations of researchers to spread skills (European Commission 2012). Further, leading research institutes are demanding innovative solutions that combine knowledge from different scientific disciplines (National Academies 2004).

  2. In the following part, affiliation(s) always refers to the departmental affiliation(s) listed by an author.

  3. The cross-citation matrix of all SCs (1991–2015) was constructed by Lin Zhang based on an in-house database of the Centre for R&D Monitoring (ECOOM), Belgium.

  4. Some experiments were tried before we set the threshold of 60%. Compared to other thresholds, for instances, 70% or 80%, the threshold of 60% provides a much more balanced distribution of publications among the three sub-datasets.

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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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Authors and Affiliations

  1. School of Information Management, Wuhan University, Wuhan, China

    Lin Zhang

  2. Department MSI, Centre for R&D Monitoring (ECOOM), KU Leuven, Leuven, Belgium

    Lin Zhang

  3. Department of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, China

    Lin Zhang, Beibei Sun & Lixin Chen

  4. Institute of Policies and Public Goods, Spanish National Research Council (CSIC-IPP), Madrid, Spain

    Zaida Chinchilla-Rodríguez

  5. Department of Public Administration, Hunan University, Changsha, China

    Ying Huang

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Correspondence to Lin Zhang or Ying Huang.

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Zhang, L., Sun, B., Chinchilla-Rodríguez, Z. et al. Interdisciplinarity and collaboration: on the relationship between disciplinary diversity in departmental affiliations and reference lists. Scientometrics 117, 271–291 (2018). https://doi.org/10.1007/s11192-018-2853-0

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