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Subject specialties as interdisciplinary trading grounds: the case of the social sciences and humanities

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Abstract

In this study we explore the disciplinary diversity present within subject specialties in the social sciences and humanities. Subject specialties are operationalized as textually coherent clusters of documents. We apply topic modelling to textual information on the individual document level (titles and abstracts) to cluster a multilingual set of roughly 45,000 documents into subject specialties. The dataset includes the metadata of journal articles, conference proceedings, book chapters, and monographs. We make use of two indicators, namely, the organizational affiliation based on the departmental address of the authors and the cognitive orientation based on the disciplinary classifications at the publication level. First, we study the disciplinary diversity of the clusters by calculating a Hill-type diversity index. We draw an overall picture of the distribution of subject specialties over diversity scores and contrast the two indicators with each other. The goal is to discover whether some subject specialties are inherently multi- or interdisciplinary in nature, and whether the different indicators are telling a well-aligned, similar story. Second, for each cluster of documents we calculate the dominance, i.e. the relative size of the largest discipline. This proxy of disciplinary concentration gives an idea of the extent to which a specialty is disciplined. The results show that all subject specialties analyzed serve as interdisciplinary trading grounds, with outliers in both directions of the disciplinary-interdisciplinary continuum. For a large share of specialties, the dominant cognitive and organizational disciplinary classification were found to be well aligned. We present a typology of subject specialties by contrasting the organizational and cognitive diversity scores.

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Availability of data and code

Notebook and data to be published on Github: https://github.com/JoshuaE1/interdisciplinarity-subject-specialties-SSH.

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Acknowledgements

This paper is a substantially extended version of a research in progress paper presented at the ISSI2021 conference titled ‘Clustering social sciences and humanities publications: Can word and document embeddings improve cluster quality?’ (Eykens, Guns, & Engels, 2021). We would like to thank Hongyu Zhou for his suggestions made about the visualization which helped improve this paper. 

Funding

This investigation has been made possible by the financial support of the Flemish government to ECOOM.

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Authors and Affiliations

  1. Centre for R&D Monitoring (ECOOM), Faculty of Social Sciences, University of Antwerp, Antwerp, Belgium

    Joshua Eykens & Raf Guns

  2. Department of Sociology, Ghent University, Ghent, Belgium

    Raf Vanderstraeten

  3. Department of Sociology, The London School of Economics and Political Science, London, UK

    Raf Vanderstraeten

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  1. Joshua Eykens
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  2. Raf Guns
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  3. Raf Vanderstraeten
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Contributions

JE, RG, RV: Conceptualization, JE, RG: Methodology, JE, RG: Software, JE: Validation, JE: Formal analysis, JE: Investigation, RG: Resources, JE, RG: Data curation, JE, RV: Writing—Original draft, JE, RG, RV: Writing—Review and editing, JE, RG: Visualization, JE, RG: Supervision, JE: Project administration, RG: Funding acquisition.

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Correspondence to Joshua Eykens.

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Eykens, J., Guns, R. & Vanderstraeten, R. Subject specialties as interdisciplinary trading grounds: the case of the social sciences and humanities. Scientometrics 127, 7193–7213 (2022). https://doi.org/10.1007/s11192-021-04254-w

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  • DOI: https://doi.org/10.1007/s11192-021-04254-w

Keywords

Mathematical Subject Classification

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