A scientometric analysis of the emerging topics in general computer science

Citations have been an acceptable journal performance metric used by many indexing databases for inclusion and discontinuation of journals in their list. Therefore, editorial teams must maintain their journal performance by increasing article citations for continuous content indexing in the databas...

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Bibliographic Details
Main Authors: Katuk, Norliza, Ku-Mahamud, Ku Ruhana, Zakaria, Nur Haryani, Jabbar, Ayad Mohammed
Format: Article
Language:English
Published: Universiti Utara Malaysia Press 2020
Subjects:
Online Access:http://repo.uum.edu.my/27851/1/JICT%2019%204%202020%20583-622.pdf
http://repo.uum.edu.my/27851/
http://www.jict.uum.edu.my/index.php/previous-issues/173-journal-of-information-and-communication-technology-jict-vol-19-no-4-october-2020#a6
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Summary:Citations have been an acceptable journal performance metric used by many indexing databases for inclusion and discontinuation of journals in their list. Therefore, editorial teams must maintain their journal performance by increasing article citations for continuous content indexing in the databases. With this aim in hand, this study intended to assist the editorial team of the Journal of Information and Communication Technology (JICT) in increasing the performance and impact of the journal. Currently, the journal has suffered from low citation count, which may jeopardise its sustainability. Past studies in library science suggested a positive correlation between keywords and citations. Therefore, keyword and topic analyses could be a solution to address the issue of journal citation. This article described a scientometric analysis of emerging topics in general computer science, the Scopus subject area for which JICT is indexed. This study extracted bibliometric data of the top 10% journals in the subject area to create a dataset of 5,546 articles. The results of the study suggested ten emerging topics in computer science that can be considered by the journal editorial team in selecting articles and a list of highly used keywords in articles published in 2019 and 2020 (as of 15 April 2020). The outcome of this study might be considered by the JICT editorial team and other journals in general computer science that suffer from a similar issue.