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Scientific Collaboration, Citation and Topic Analysis of International Conference on Agile Software Development Papers
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdańsk, Poland. (SQUAD - SOFTWARE QUALITY AND DIGITAL MODERNISATION)ORCID iD: 0000-0002-7885-0369
M3S Research Unit, University of Oulu, Oulu, Finland.
2019 (English)In: Advances in Agile and User-Centred Software Engineering, Springer, 2019, p. 108-132Chapter in book (Refereed)
Abstract [en]

The International Conference on Agile Software Development (XP) was established almost sixteen years ago. Based on data from Scopus database, a total of 789 papers have been published in between years of 2002 and 2018. We employed bibliometrics analysis and topic modeling with R/RStudio to analyze these published papers from various dimensions, including the most active authors, collaboration of authorship, most cited papers, used keywords and trends of probable topics from the titles and abstracts of those papers. The results show that the first five years of XP conference cover nearly 40% of the papers published until now and almost 62% of the XP papers have been cited at least once. Mining of XP conference paper titles and abstracts result in these hot research topics: “Coordination”, “Technical Debt”, “Teamwork”, “Startups” and “Agile Practices”, thus strongly focusing on practical issues and problems faced by the practitioners in the industry. The results highlight the most influential researchers and institutions, and the collaboration between the authors in the conference papers. The approach applied in this study can be extended to other software engineering venues and can be applied to large-scale studies.

Place, publisher, year, edition, pages
Springer, 2019. p. 108-132
Series
Lecture Notes in Business Information Processing
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-77123DOI: 10.1007/978-3-030-37534-8_6ISI: 000653746800006ISBN: 978-3-030-37534-8 (electronic)ISBN: 978-3-030-37533-1 (print)OAI: oai:DiVA.org:kau-77123DiVA, id: diva2:1410761
Available from: 2020-03-01 Created: 2020-03-01 Last updated: 2021-06-22Bibliographically approved

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Publisher's full texthttps://link.springer.com/chapter/10.1007/978-3-030-37534-8_6

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Ahmad, Muhammad Ovais

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CiteExportLink to record
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