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Role of interdisciplinarity in computer sciences: quantification, impact and life trajectory

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  • Tanmoy Chakraborty

    (Indraprastha Institute of Information Technology, Delhi (IIIT-D))

Abstract

The tremendous advances in computer science in the last few decades have provided the platform to address and solve complex problems using interdisciplinary research. In this paper, we investigate how the extent of interdisciplinarity in computer science domain (which is further divided into 24 research fields) has changed over the last 50 years. To this end, we collect a massive bibliographic dataset with rich metadata information. We start with quantifying interdisciplinarity of a field in terms of the diversity of topics and citations. We then analyze the effect of interdisciplinary research on the scientific impact of individual fields and observe that highly disciplinary and highly interdisciplinary papers in general have a low scientific impact; remarkably those that are able to strike a balance between the two extremes eventually land up having the highest impact. Further, we study the reciprocity among fields through citation interactions and notice that links from one field to related and citation-intensive fields (fields producing large number of citations) are reciprocated heavily. A systematic analysis of the citation interactions reveals the life trajectory of a research field, which generally undergoes three phases—a growing phase, a matured phase and an interdisciplinary phase. The combination of metrics and empirical observations presented here provides general benchmarks for future studies of interdisciplinary research activities in other domains of science.

Suggested Citation

  • Tanmoy Chakraborty, 2018. "Role of interdisciplinarity in computer sciences: quantification, impact and life trajectory," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 1011-1029, March.
    • Handle: RePEc:spr:scient:v:114:y:2018:i:3:d:10.1007_s11192-017-2628-z
    DOI: 10.1007/s11192-017-2628-z
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    1. Keungoui Kim & Dieter F. Kogler & Sira Maliphol, 2024. "Identifying interdisciplinary emergence in the science of science: combination of network analysis and BERTopic," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    2. 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.
    3. Xiaoguang Wang & Hongyu Wang & Han Huang, 2021. "Evolutionary exploration and comparative analysis of the research topic networks in information disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4991-5017, June.
    4. Steffen Wendzel & Cédric Lévy-Bencheton & Luca Caviglione, 2020. "Not all areas are equal: analysis of citations in information security research," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 267-286, January.
    5. Erin Leahey & Sondra N. Barringer & Misty Ring-Ramirez, 2019. "Universities’ structural commitment to interdisciplinary research," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 891-919, March.
    6. Sitaram Devarakonda & Dmitriy Korobskiy & Tandy Warnow & George Chacko, 2020. "Viewing computer science through citation analysis: Salton and Bergmark Redux," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 271-287, October.
    7. Mao, Jin & Liang, Zhentao & Cao, Yujie & Li, Gang, 2020. "Quantifying cross-disciplinary knowledge flow from the perspective of content: Introducing an approach based on knowledge memes," Journal of Informetrics, Elsevier, vol. 14(4).

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