“…From the graph, we see that the best dimension reduction achieved for the first two dimensions of the MCA account for roughly 72% of the total variability. In this graph, the closer the dots, the similar the profile they represent, whereas each cluster of dots represents discriminating profiles [ 64 ]. Fig.…”
Since its inception, YouTube has been a source of entertainment and education. Everyday millions of videos are uploaded to this platform. Researchers have been using YouTube as a source of information in their research. However, there is a lack of bibliometric reports on research carried out on this platform and the pattern in the published works. This study aims at providing a bibliometric analysis on YouTube as a source of information to fill this gap. Specifically, this paper analyzes 1781 articles collected from the Scopus database spanning fifteen years. The analysis revealed that 2006-2007 were initial stage in YouTube research followed by 2008 -2017 which is the decade of rapid growth in YouTube research. The 2017 -2021 is considered the stage of consolidation and stabilization of this research topic. We also discovered that most relevant papers were published in small number of journals such as New Media and Society, Convergence, Journal of Medical Internet Research, Computers in Human Behaviour and the Physics Teacher, which proves the Bradford’s law. USA, Turkey, and UK are the countries with the highest number of publications. We also present network analysis between countries, sources, and authors. Analyzing the keywords resulted in finding the trend in research such as “video sharing” (2010-2018), “web -based learning” (2012-2014), and “COVID -19” (2020 onward). Finally, we used Multiple Correspondence Analysis (MCA) to find the conceptual clusters of research on YouTube. The first cluster is related to user -generated content. The second cluster is about health and medical issues, and the final cluster is on the topic of information quality.
“…From the graph, we see that the best dimension reduction achieved for the first two dimensions of the MCA account for roughly 72% of the total variability. In this graph, the closer the dots, the similar the profile they represent, whereas each cluster of dots represents discriminating profiles [ 64 ]. Fig.…”
Since its inception, YouTube has been a source of entertainment and education. Everyday millions of videos are uploaded to this platform. Researchers have been using YouTube as a source of information in their research. However, there is a lack of bibliometric reports on research carried out on this platform and the pattern in the published works. This study aims at providing a bibliometric analysis on YouTube as a source of information to fill this gap. Specifically, this paper analyzes 1781 articles collected from the Scopus database spanning fifteen years. The analysis revealed that 2006-2007 were initial stage in YouTube research followed by 2008 -2017 which is the decade of rapid growth in YouTube research. The 2017 -2021 is considered the stage of consolidation and stabilization of this research topic. We also discovered that most relevant papers were published in small number of journals such as New Media and Society, Convergence, Journal of Medical Internet Research, Computers in Human Behaviour and the Physics Teacher, which proves the Bradford’s law. USA, Turkey, and UK are the countries with the highest number of publications. We also present network analysis between countries, sources, and authors. Analyzing the keywords resulted in finding the trend in research such as “video sharing” (2010-2018), “web -based learning” (2012-2014), and “COVID -19” (2020 onward). Finally, we used Multiple Correspondence Analysis (MCA) to find the conceptual clusters of research on YouTube. The first cluster is related to user -generated content. The second cluster is about health and medical issues, and the final cluster is on the topic of information quality.
“…Software engineering is a complex technical, knowledge-based task that requires focused, uninterrupted work while still coordinating and collaborating with other developers and stakeholders (Nakagawa et al, 2021). This entails intense periods of coordination, collaboration, and communication while managing intricate dependencies within and across systems in order to effectively develop highquality, complex software (Wong, Mittas, Arvanitou, & Li, 2021). In order to manage the collaborative nature of software engineering, engineering tools e.g.…”
Section: Epic Series In Computingmentioning
confidence: 99%
“…Software analysis techniques for performance and optimizing parallel code on multicore/many core systems; parallelization approach for embedded heterogeneous systems; software parallelization; domainspecific language for some specific parallel systems (Giray, 2021;Wong et al, 2021) C08+ Business knowledge / business life; Digitalization; Knowledge economy; Human factors in software engineering (Angelopoulos et al, 2019;Çakmak, 2018;Gekara et al, 2020;Nakagawa et al, 2021;Tura, 2020 (Ford et al, 2021;Gekara et al, 2020;Giray, 2021), V06 Ethics (Groeneveld, Vennekens, & Aerts, 2019;Porzelt, 2020) In total 11 cognitive skills, 7 motivational skills, 3 social skill types and 6 volitional skills were extracted from the academic literature dataset.…”
Section: C07+mentioning
confidence: 99%
“…The software development and -engineering industry is one of the fastest-growing trades worldwide comprising of a wide variety of applications (Wong et al, 2021). In Society 5.0, with its strong focus on human-centeredness (Fukuyama, 2018), technology should not be the point of friction between these applications, its product and users.…”
Section: Introductionmentioning
confidence: 99%
“…In Society 5.0, with its strong focus on human-centeredness (Fukuyama, 2018), technology should not be the point of friction between these applications, its product and users. Designers, software engineers and developers need to help users to streamline, simplify, evaluate and filter human-computer interaction, through becoming more human-oriented and better understand human needs, emotions and human behavior (Groeneveld, Vennekens, & Aerts, 2019;Wong et al, 2021).…”
Society 5.0, with all its different cyber-physical aspects not only presents a technical challenge, but also significantly changes the structures and business processes of organizations. It requires software engineers and developers to consider a new level of socio-technical interaction and planning. Software should not be the point of friction among products, services and users, but should rather encourage software engineers and developers to become more human-oriented. Therefore, the purpose of this study was to investigate the future of work skills in Society 5.0 for software engineers and developers. We collected and analyzed two datasets; one dataset containing academic peer reviewed publications and the second dataset encompassed popular press articles that predicted the future of software engineering and development. We used the Software Engineering Body of Knowledge (SWEBOK) to map the data and found that future of work skills for software engineers and developers are driven by software foundations and the evolution of new programming languages and technologies e.g. quantum computing. In addition, software professional practices such as containerization, no / low-code development and fast innovation / prototyping cycles will affect the future of work together with software development practices such as cross-platform development, continuous integration and deployment, and cybersecurity. Based on the findings, we developed a skills evaluation tool that could be used to establish a future of work skills profile. By considering the evolution of the software engineering and –development role, as well as the future requirement due to technology evolution, a software engineer and developer may be able to prepare themselves for the Society 5.0 domain.
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