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Not all areas are equal: analysis of citations in information security research

Author

Listed:
  • Steffen Wendzel

    (Worms University of Applied Sciences
    Fraunhofer FKIE)

  • Cédric Lévy-Bencheton

    (Cetome)

  • Luca Caviglione

    (Institute for Applied Mathematics and Information Technologies)

Abstract

The understanding of the inner workings of a research community is essential to evaluate the impact of an author as well as to decide where and how to publish results. One of the key metrics is the number of citations that a publication receives. In parallel, information security is now a key and strategic area, partially fueled by the advent of the Internet of Things (IoT) and the need of pursuing cybercriminals by using digital forensics techniques. Therefore, this paper analyzes several factors influencing the number of citations in the domain of information security, such as differences between journal and conference publications, or the impact of the number of pages and the length of the abstract. To obtain quantitative results, we investigated papers of six sub-disciplines, i.e., anonymity and privacy, cryptography, information hiding, IoT and Cyber-Physical System security, digital forensics and incident response, and network security. For each sub-domain, we used metadata of 5000 publications collected from IEEE-Xplore. Results indicate some clear behaviors, for instance, papers tend to receive more citations when their abstract is longer and the number of references positively influences the performance of the work.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:122:y:2020:i:1:d:10.1007_s11192-019-03279-6
    DOI: 10.1007/s11192-019-03279-6
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    References listed on IDEAS

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    1. Si Shen & Ronald Rousseau & Dongbo Wang, 2018. "Do papers with an institutional e-mail address receive more citations than those with a non-institutional one?," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 1039-1050, May.
    2. Lutz Bornmann & Loet Leydesdorff, 2018. "Count highly-cited papers instead of papers with h citations: use normalized citation counts and compare “like with like”!," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 1119-1123, May.
    3. João M. Fernandes & Miguel P. Monteiro, 2017. "Evolution in the number of authors of computer science publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 529-539, February.
    4. Munan Li, 2018. "Classifying and ranking topic terms based on a novel approach: role differentiation of author keywords," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 77-100, July.
    5. Kayvan Kousha & Mike Thelwall, 2007. "Google Scholar citations and Google Web/URL citations: A multi‐discipline exploratory analysis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(7), pages 1055-1065, May.
    6. Sun, Xiaoling & Ding, Kun & Lin, Yuan, 2016. "Mapping the evolution of scientific fields based on cross-field authors," Journal of Informetrics, Elsevier, vol. 10(3), pages 750-761.
    7. Myriam Dunn Cavelty, 2018. "Cybersecurity Research Meets Science and Technology Studies," Politics and Governance, Cogitatio Press, vol. 6(2), pages 22-30.
    8. Waleed Iqbal & Junaid Qadir & Gareth Tyson & Adnan Noor Mian & Saeed-ul Hassan & Jon Crowcroft, 2019. "A bibliometric analysis of publications in computer networking research," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1121-1155, May.
    9. 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.
    10. Bei-Ni Yan & Tian-Shyug Lee & Tsung-Pei Lee, 2015. "Mapping the intellectual structure of the Internet of Things (IoT) field (2000–2014): a co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(2), pages 1285-1300, November.
    11. Dalibor Fiala & Gabriel Tutoky, 2017. "Computer Science Papers in Web of Science: A Bibliometric Analysis," Publications, MDPI, vol. 5(4), pages 1-16, September.
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