IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v119y2019i2d10.1007_s11192-019-03086-z.html
   My bibliography  Save this article

A bibliometric analysis of publications in computer networking research

Author

Listed:
  • Waleed Iqbal

    (Information Technology University)

  • Junaid Qadir

    (Information Technology University)

  • Gareth Tyson

    (Queen Mary University of London)

  • Adnan Noor Mian

    (Information Technology University
    University of Cambridge)

  • Saeed-ul Hassan

    (Information Technology University)

  • Jon Crowcroft

    (University of Cambridge)

Abstract

Computer networking is a major research discipline in computer science, electrical engineering, and computer engineering. The field has been actively growing, in terms of both research and development, for the past hundred years. This study uses the article content and metadata of four important computer networking periodicals—IEEE Communications Surveys and Tutorials (COMST), IEEE/ACM Transactions on Networking (TON), ACM Special Interest Group on Data Communications (SIGCOMM), and IEEE International Conference on Computer Communications (INFOCOM)—obtained using ACM, IEEE Xplore, Scopus and CrossRef, for an 18-year period (2000–2017) to address important bibliometrics questions. All of the venues are prestigious, yet they publish quite different research. The first two of these periodicals (COMST and TON) are highly reputed journals of the fields while SIGCOMM and INFOCOM are considered top conferences of the field. SIGCOMM and INFOCOM publish new original research. TON has a similar genre and publishes new original research as well as the extended versions of different research published in the conferences such as SIGCOMM and INFOCOM, while COMST publishes surveys and reviews (which not only summarize previous works but highlight future research opportunities). In this study, we aim to track the co-evolution of trends in the COMST and TON journals and compare them to the publication trends in INFOCOM and SIGCOMM. Our analyses of the computer networking literature include: (a) metadata analysis; (b) content-based analysis; and (c) citation analysis. In addition, we identify the significant trends and the most influential authors, institutes and countries, based on the publication count as well as article citations. Through this study, we are proposing a methodology and framework for performing a comprehensive bibliometric analysis on computer networking research. To the best of our knowledge, no such study has been undertaken in computer networking until now.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:119:y:2019:i:2:d:10.1007_s11192-019-03086-z
    DOI: 10.1007/s11192-019-03086-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-019-03086-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-019-03086-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhifeng Yin & Qiang Zhi, 2017. "Dancing with the academic elite: a promotion or hindrance of research production?," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 17-41, January.
    2. 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.
    3. Gustavo Cattelan Nobre & Elaine Tavares, 2017. "Scientific literature analysis on big data and internet of things applications on circular economy: a bibliometric study," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 463-492, April.
    4. Caroline S. Wagner & Travis A. Whetsell & Loet Leydesdorff, 2017. "Growth of international collaboration in science: revisiting six specialties," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1633-1652, March.
    5. Miloš Savić & Mirjana Ivanović & Bojana Dimić Surla, 2017. "Analysis of intra-institutional research collaboration: a case of a Serbian faculty of sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 195-216, January.
    6. Xiaodan Zhu & Peter Turney & Daniel Lemire & André Vellino, 2015. "Measuring academic influence: Not all citations are equal," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(2), pages 408-427, February.
    7. Saeed-Ul Hassan & Mubashir Imran & Uzair Gillani & Naif Radi Aljohani & Timothy D. Bowman & Fereshteh Didegah, 2017. "Measuring social media activity of scientific literature: an exhaustive comparison of scopus and novel altmetrics big data," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 1037-1057, November.
    8. Fereshteh Didegah & Mike Thelwall, 2018. "Co‐saved, co‐tweeted, and co‐cited networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(8), pages 959-973, August.
    9. Hajdeja Iglič & Patrick Doreian & Luka Kronegger & Anuška Ferligoj, 2017. "With whom do researchers collaborate and why?," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 153-174, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hu, Ya-Han & Tai, Chun-Tien & Liu, Kang Ernest & Cai, Cheng-Fang, 2020. "Identification of highly-cited papers using topic-model-based and bibliometric features: the consideration of keyword popularity," Journal of Informetrics, Elsevier, vol. 14(1).
    2. 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.
    3. Guo Chen & Jing Chen & Yu Shao & Lu Xiao, 2023. "Automatic noise reduction of domain-specific bibliographic datasets using positive-unlabeled learning," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1187-1204, February.
    4. Eitan Frachtenberg, 2022. "Multifactor Citation Analysis over Five Years: A Case Study of SIGMETRICS Papers," Publications, MDPI, vol. 10(4), pages 1-16, December.
    5. Li Zhao & Zhi-ying Tang & Xin Zou, 2019. "Mapping the Knowledge Domain of Smart-City Research: A Bibliometric and Scientometric Analysis," Sustainability, MDPI, vol. 11(23), pages 1-28, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chaocheng He & Jiang Wu & Qingpeng Zhang, 2021. "Characterizing research leadership on geographically weighted collaboration network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4005-4037, May.
    2. Anwar Said & Timothy D. Bowman & Rabeeh Ayaz Abbasi & Naif Radi Aljohani & Saeed-Ul Hassan & Raheel Nawaz, 2019. "Mining network-level properties of Twitter altmetrics data," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 217-235, July.
    3. Marian-Gabriel Hâncean & Matjaž Perc & Jürgen Lerner, 2021. "The coauthorship networks of the most productive European researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 201-224, January.
    4. Saeed-Ul Hassan & Naif R. Aljohani & Mudassir Shabbir & Umair Ali & Sehrish Iqbal & Raheem Sarwar & Eugenio Martínez-Cámara & Sebastián Ventura & Francisco Herrera, 2020. "Tweet Coupling: a social media methodology for clustering scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 973-991, August.
    5. Xie, Qing & Zhang, Xinyuan & Kim, Giyeong & Song, Min, 2022. "Exploring the influence of coauthorship with top scientists on researchers’ affiliation, research topic, productivity, and impact," Journal of Informetrics, Elsevier, vol. 16(3).
    6. Uwe Cantner & Martin Kalthaus & Matthias Menter & Pierre Mohnen, 2023. "Global knowledge flows: characteristics, determinants, and impacts," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 32(5), pages 1063-1076.
    7. Faiza Qayyum & Harun Jamil & Naeem Iqbal & DoHyeun Kim & Muhammad Tanvir Afzal, 2022. "Toward potential hybrid features evaluation using MLP-ANN binary classification model to tackle meaningful citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6471-6499, November.
    8. Lu, Wei & Ren, Yan & Huang, Yong & Bu, Yi & Zhang, Yuehan, 2021. "Scientific collaboration and career stages: An ego-centric perspective," Journal of Informetrics, Elsevier, vol. 15(4).
    9. Tuba Bircan & Almila Alkim Akdag Salah, 2022. "A Bibliometric Analysis of the Use of Artificial Intelligence Technologies for Social Sciences," Mathematics, MDPI, vol. 10(23), pages 1-17, November.
    10. Ying Guo & Xiantao Xiao, 2022. "Author-level altmetrics for the evaluation of Chinese scholars," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 973-990, February.
    11. Hans Pohl, 2021. "Internationalisation, innovation, and academic–corporate co-publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1329-1358, February.
    12. Yi Bu & Binglu Wang & Win-bin Huang & Shangkun Che & Yong Huang, 2018. "Using the appearance of citations in full text on author co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 275-289, July.
    13. Hans Pohl, 2024. "Using citation-based indicators to compare bilateral research collaborations," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(8), pages 4751-4770, August.
    14. Yaxue Ma & Zhichao Ba & Yuxiang Zhao & Jin Mao & Gang Li, 2021. "Understanding and predicting the dissemination of scientific papers on social media: a two-step simultaneous equation modeling–artificial neural network approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 7051-7085, August.
    15. Zhai, Li & Yan, Xiangbin, 2022. "A directed collaboration network for exploring the order of scientific collaboration," Journal of Informetrics, Elsevier, vol. 16(4).
    16. Fabio De Felice & Antonella Petrillo, 2021. "Green Transition: The Frontier of the Digicircular Economy Evidenced from a Systematic Literature Review," Sustainability, MDPI, vol. 13(19), pages 1-26, October.
    17. Broccardo, Laura & Zicari, Adrián & Jabeen, Fauzia & Bhatti, Zeeshan A., 2023. "How digitalization supports a sustainable business model: A literature review," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    18. Fazal Ur Rehman & Basheer M. Al-Ghazali & Adel Ghaleb Haddad & Ehab Abdullatif Qahwash & M. Sadiq Sohail, 2023. "Exploring the Reverse Relationship between Circular Economy Innovation and Digital Sustainability—The Dual Mediation of Government Incentives," Sustainability, MDPI, vol. 15(6), pages 1-21, March.
    19. Marek Kwiek, 2018. "High research productivity in vertically undifferentiated higher education systems: Who are the top performers?," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 415-462, April.
    20. Iraklis Varlamis & Dimitrios Michail & Foteini Glykou & Panagiotis Tsantilas, 2022. "A Survey on the Use of Graph Convolutional Networks for Combating Fake News," Future Internet, MDPI, vol. 14(3), pages 1-19, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:119:y:2019:i:2:d:10.1007_s11192-019-03086-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.