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Identifying interdisciplinarity through the disciplinary classification of coauthors of scientific publications

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  • Giovanni Abramo
  • Ciriaco Andrea D'Angelo
  • Flavia Di Costa

Abstract

The growing complexity of challenges involved in scientific progress demands ever more frequent application of competencies and knowledge from different scientific fields. The present work analyzes the degree of collaboration among scientists from different disciplines to identify the most frequent “combinations of knowledge” in research activity. The methodology adopts an innovative bibliometric approach based on the disciplinary affiliation of publication coauthors. The field of observation includes all publications (167,179) indexed in the Science Citation Index Expanded for the years 2004–2008, authored by all scientists in the hard sciences (43,223) at Italian universities (68). The analysis examines 205 research fields grouped in 9 disciplines. Identifying the fields with the highest potential of interdisciplinary collaboration is useful to inform research polices at the national and regional levels, as well as management strategies at the institutional level.

Suggested Citation

  • Giovanni Abramo & Ciriaco Andrea D'Angelo & Flavia Di Costa, 2012. "Identifying interdisciplinarity through the disciplinary classification of coauthors of scientific publications," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(11), pages 2206-2222, November.
    • Handle: RePEc:bla:jamist:v:63:y:2012:i:11:p:2206-2222
    DOI: 10.1002/asi.22647
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    Cited by:

    1. Hamid R. Jamali & Ghasem Azadi-Ahmadabadi & Saeid Asadi, 2018. "Interdisciplinary relations of converging technologies: Nano–Bio–Info–Cogno (NBIC)," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 1055-1073, August.
    2. Ugo Moschini & Elena Fenialdi & Cinzia Daraio & Giancarlo Ruocco & Elisa Molinari, 2020. "A comparison of three multidisciplinarity indices based on the diversity of Scopus subject areas of authors’ documents, their bibliography and their citing papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1145-1158, November.
    3. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Zhang, Lin, 2018. "A comparison of two approaches for measuring interdisciplinary research output: The disciplinary diversity of authors vs the disciplinary diversity of the reference list," Journal of Informetrics, Elsevier, vol. 12(4), pages 1182-1193.
    4. Wolfgang Glänzel & Koenraad Debackere, 2022. "Various aspects of interdisciplinarity in research and how to quantify and measure those," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5551-5569, September.
    5. Shiji Chen & Clément Arsenault & Yves Gingras & Vincent Larivière, 2015. "Exploring the interdisciplinary evolution of a discipline: the case of Biochemistry and Molecular Biology," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1307-1323, February.
    6. Yu-Wei Chang, 2019. "Are articles in library and information science (LIS) journals primarily contributed to by LIS authors?," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 81-104, October.
    7. Carusi, Chiara & Bianchi, Giuseppe, 2019. "Scientific community detection via bipartite scholar/journal graph co-clustering," Journal of Informetrics, Elsevier, vol. 13(1), pages 354-386.
    8. Casey Helgeson & Robert E. Nicholas & Klaus Keller & Chris E. Forest & Nancy Tuana, 2022. "Attention to values helps shape convergence research," Climatic Change, Springer, vol. 170(1), pages 1-19, January.
    9. Sasaki, Hajime & Sakata, Ichiro, 2021. "Identifying potential technological spin-offs using hierarchical information in international patent classification," Technovation, Elsevier, vol. 100(C).
    10. Bei Zeng & Haihua Lyu & Zhenyue Zhao & Jiang Li, 2021. "Exploring the direction and diversity of interdisciplinary knowledge diffusion: A case study of professor Zeyuan Liu's scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6253-6272, July.
    11. Cristóbal Urbano & Jordi Ardanuy, 2020. "Cross-disciplinary collaboration versus coexistence in LIS serials: analysis of authorship affiliations in four European countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 575-602, July.
    12. Amar Dhand & Douglas A Luke & Bobbi J Carothers & Bradley A Evanoff, 2016. "Academic Cross-Pollination: The Role of Disciplinary Affiliation in Research Collaboration," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-13, January.
    13. Cantone, Giulio Giacomo, 2024. "How to measure interdisciplinary research? A systematic, yet critical, review," MetaArXiv hva4p, Center for Open Science.
    14. Tracy Klarenbeek & Nelius Boshoff, 2018. "Measuring multidisciplinary health research at South African universities: a comparative analysis based on co-authorships and journal subject categories," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1461-1485, September.
    15. Alfonso Ávila-Robinson & Cristian Mejia & Shintaro Sengoku, 2021. "Are bibliometric measures consistent with scientists’ perceptions? The case of interdisciplinarity in research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7477-7502, September.
    16. Xiaowen Xi & Jiaqi Wei & Ying Guo & Weiyu Duan, 2022. "Academic collaborations: a recommender framework spanning research interests and network topology," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6787-6808, November.
    17. Pertti Vakkari & Yu‐Wei Chang & Kalervo Järvelin, 2022. "Disciplinary contributions to research topics and methodology in Library and Information Science—Leading to fragmentation?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(12), pages 1706-1722, December.
    18. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Murgia, Gianluca, 2013. "The collaboration behaviors of scientists in Italy: A field level analysis," Journal of Informetrics, Elsevier, vol. 7(2), pages 442-454.
    19. Mehdi Rhaiem & Nabil Amara, 2020. "Determinants of research efficiency in Canadian business schools: evidence from scholar-level data," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 53-99, October.
    20. Zhichao Ba & Yujie Cao & Jin Mao & Gang Li, 2019. "A hierarchical approach to analyzing knowledge integration between two fields—a case study on medical informatics and computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1455-1486, June.
    21. Hoang-Son Pham & Bram Vancraeynest & Hanne Poelmans & Sadia Vancauwenbergh & Amr Ali-Eldin, 2023. "Identifying interdisciplinary research in research projects," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5521-5544, October.
    22. Lin Zhang & Beibei Sun & Zaida Chinchilla-Rodríguez & Lixin Chen & Ying Huang, 2018. "Interdisciplinarity and collaboration: on the relationship between disciplinary diversity in departmental affiliations and reference lists," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 271-291, October.
    23. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Costa, 2017. "Specialization versus diversification in research activities: the extent, intensity and relatedness of field diversification by individual scientists," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1403-1418, September.
    24. Bart Thijs, 2020. "Using neural-network based paragraph embeddings for the calculation of within and between document similarities," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 835-849, November.

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