Annals of Library and Information Studies

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Collaborative Authorship Patterns in Computer Science Publications


Affiliations
1 Research Scholar, Data to Knowledge (D2K) Lab, School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi 110 067, India., India
2 Professor, Data to Knowledge (D2K) Lab, School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi 110 067, India., India
 

Based on the analysis of data we observe that the share of single-authored papers was significantly high in theoretical computer science, while collaborative efforts dominate computer science system research like PL, AI, ML, etc. Collaborative authorship is higher in journals over conferences. Further, values of collaborative indicators are also high for journals except for the Machine Learning (ML) subfield. In addition, the author distribution patterns are different for conferences and journals. The findings also exhibited diversity in authorship trends across sub-fields of CS research. Our results show collaboration trends in conferences and journals of major CS subfields. Such collaborative patterns benefit the funding agency, policymakers, scientific community, and researchers to plan and execute their research.

Keywords

Research Collaboration, Co-authorship, Computer Science, Conferences Journals.
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  • Melin G and Persson O, Studying research collaboration using co-authorships, Scientometrics, 36(3) (1996) 363-377.

  • Franceschet M and Costantini A, The effect of scholar collaboration on impact and quality of academic papers, Journal of informetrics, 4(4) (2010) 540-553.

  • Sooryamoorthy R, Collaboration and publication: How collaborative are scientists in South Africa?, Scientometrics, 80(2) (2009) 419-439.

  • Ibanez A, Bielza C and Larranaga P, Relationship among research collaboration, number of documents and number of citations: a case study in Spanish computer science production in 2000–2009, Scientometrics, 95(2) (2013) 689-716.

  • Laudel G, What do we measure by co-authorships?, Research evaluation, 11(1) (2002) 3-15.

  • Fernandes J M, Authorship trends in software engineering, Scientometrics, 101(1) (2014) 257-271.

  • Jokić M, Productivity, visibility, authorship, and collaboration in library and information science journals: Central and Eastern European authors, Scientometrics, 122(2) (2020) 1189-1219.

  • Franceschet M, Collaboration in computer science: A network science approach, Journal of the American Society for Information Science and Technology , 62(10) (2011) 1992-2012.

  • Gazni A and Didegah F, Investigating different types of research collaboration and citation impact: a case study of Harvard University's publications, Scientometrics, 87(2) (2011) 251-265.

  • Singh V K, Uddin A and Pinto D, Computer science research: The top 100 institutions in India and in the world, Scientometrics, 104(2) (2015) 529-553.

  • Mukherjee B and Tiwari P, Research Collaboration as perceived by Top-performing Engineering Institutes of India, Annals of Library and Information Studies, 69(4) (2022).

  • Fat MO, Mo-Index for Multi-Authors Papers, Annals of Library and Information Studies, 69(4) (2022).

  • Ronda-Pupo G A, The effect of document types and sizes on the scaling relationship between citations and co-authorship patterns in management journals, Scientometrics, 110(3) (2017) 1191–1207.

  • Fan L, Wang Y, Ding S and Qi B, Productivity trends and citation impact of different institutional collaboration patterns at the research units' level, Scientometrics, 125(2) (2020) 1179–1196.

  • Kumari P and Kumar R, Scientometric analysis of computer science publications in journals and conferences with publication patterns, Journal of Scientometric Research, 9(1) (2020) 54–62.

  • Freyne J, Coyle L, Smyth B, and Cunningham P, Relative status of journal and conference publications in computer science, Communications of the ACM, 53(11) (2010) 124– 132.

  • Ioannidis J P, Baas J, Klavans R and Boyack K W, A standardized citation metrics author database annotated for scientific field, PLoS biology, 17(8) (2019) e3000384.

  • Rahm E and Thor A, Citation analysis of database publications, ACM SIGMOD Record, 34(4) (2005) 48–53.

  • Barrios C, Flores E, Martınez M ́A and Ruiz-Martınez M, Is there convergence in international research collaboration? an exploration at the country level in the basic and applied science fields, Scientometrics, 120(2) (2019) 631–659.

  • Iqbal W, Qadir J, Tyson G, Mian A N, Hassan S-u, and Crowcroft J, A bibliometric analysis of publications in computer networking research, Scientometrics, 119(2) (2019) 1121–1155.

  • Kim J, Author-based analysis of conference versus journal publication in computer science, Journal Association for Information Science & Technology, 70(1) (2019) 71–82.

  • Wainer J, Eckmann M, Goldenstein S, and Rocha A, How productivity and impact differ across computer science subareas, Communications of the ACM, 56(8) (2013) 67–73.

  • Principles of Programming Languages, Available at https://www.sigplan.org/Conferences/POPL/.

  • International Conference on Machine Learning, Available at https://icml.cc/.

  • ACM Symposium on Theory of Computing, Available at http://acm-stoc.org/.

  • ACM Transactions on Programming Languages and Systems, Available at https://dl.acm.org/loi/toplas.

  • Machine Learning, Available at https://link.springer.com /journal/10994/volumes-and-issues.

  • Journal of the ACM, Available at https://dl.acm.org/loi/jacm.

  • Lawani S M, Quality, collaboration and citations in cancer research: A bibliometric study, The Florida State University, (1980).

  • Subramanyam K, Bibliometric studies of research collaboration: A review, Journal of Information Science, 6(1) (1983) 33–38.

  • Ajiferuke I, Burell Q and Tague J, Collaborative coefficient: A single measure of the degree of collaboration in research, Scientometrics, 14(5-6) (1988) 421–433.


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  • Collaborative Authorship Patterns in Computer Science Publications

Abstract Views: 158  |  PDF Views: 104

Authors

Priti Kumari
Research Scholar, Data to Knowledge (D2K) Lab, School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi 110 067, India., India
Rajeev Kumar
Professor, Data to Knowledge (D2K) Lab, School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi 110 067, India., India

Abstract


Based on the analysis of data we observe that the share of single-authored papers was significantly high in theoretical computer science, while collaborative efforts dominate computer science system research like PL, AI, ML, etc. Collaborative authorship is higher in journals over conferences. Further, values of collaborative indicators are also high for journals except for the Machine Learning (ML) subfield. In addition, the author distribution patterns are different for conferences and journals. The findings also exhibited diversity in authorship trends across sub-fields of CS research. Our results show collaboration trends in conferences and journals of major CS subfields. Such collaborative patterns benefit the funding agency, policymakers, scientific community, and researchers to plan and execute their research.

Keywords


Research Collaboration, Co-authorship, Computer Science, Conferences Journals.

References