Artículo

Bibliometrics evidences of scientific recognition in reviews and interviews theoretical notes and analysis model

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Introduction: Reviews and interviews published in scientific journals have received little attention in research in the field of Information Science. The study defends the idea that the analysis of these textual genres can demonstrate scientific recognition when they are taken as objects of study from a bibliometric perspective and analyzed based on the theoretical framework of Information Science, Sociology of Science and Linguistics. Objectives: Conduct a theoretical essay on these textual genres and develop and apply an analysis model to a sample of reviews and interviews published in Revista Estudos Feministas (REF) between 2018 and 2020. Method: Exploratory and descriptive research that uses quantitative and qualitative approaches from bibliometric and content analysis. Results: The theoretical essay highlighted the characteristics of reviews and interviews, and the analysis model developed contains indicators that signal scientific recognition: the profiles of reviews and reviewed works (n = 69), reviews (n = 81) and reviewed (n = 95); the interviews and the interviewees (n = 9), the interviewers (n = 13), as well as the academic values and attributes that are usually valued in the elaboration of these textual genres. Conclusion: The analysis of reviews and interviews published in REF based on an analysis model elaborated from an interdisciplinary perspective between Information Science, Sociology of Science and Linguistics offered an analytical toolbox relevant to the study of scientific recognition.
Hidayat, Erwin Yudi (57205439013); Hastuti, Khafiizh (56485990500); Muda, Azah Kamilah (23390362900)
Artificial intelligence in digital image processing: A bibliometric analysis
2025
10.1016/j.iswa.2024.200466
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212984349&doi=10.1016%2fj.iswa.2024.200466&partnerID=40&md5=14c2a82f6cb46e9efa80c050fc79c24f
Faculty of Computer Science, Universitas Dian Nuswantoro, Semarang, 50131, Indonesia; Dinus Research Group for AI in Medical Science (DREAMS), Universitas Dian Nuswantoro, Semarang, 50131, Indonesia; Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, 76100, Malaysia
All Open Access; Gold Open Access
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