Search

The internet has offered marketers a new way to be more creative, resulting in more openness and transparency in marketing. The proliferation of digital media platforms and the commercial use of the internet have changed the business landscape. This study uses ScientoPy to analyze the global evolution of digital marketing research. It is grounded in the eminent Scopus and Web of Science databases. The parameters examined in this study were the number of publications, the most productive author, the analysis of the author's keywords, popular sources, and institutional information. This study discovered a rising trend in digital marketing research in both the Scopus and WoS databases. "Machine Learning" has exploded in popularity during 2019 and 2020. "Digital Marketing" is inextricably linked to "Social Media", "Big Data", "Marketing Communication", "Machine Learning", and "Sentiment Analysis", all of which gained traction in 2018 and beyond. Bucharest University of Economic Studies in Romania has become the most prolific research institution on digital marketing. The findings of this study enabled readers and future researchers to identify the primary research areas, keywords, related studies, and the most notable institutions and researchers. Besides, this study provides readers and future researchers with a global perspective on hot topics in digital marketing. It offers various analyzes for well-organized information utilization. This study also illustrates recent digital marketing research trends to inform practitioners, future researchers, and policymakers about developing digital marketing research theories and practices that merit scrutiny. [ABSTRACT FROM AUTHOR]

Safety and health are intricately interwoven and have become indispensable to the thriving business world and anthropology. It is concerned with ensuring employees' physical, emotional, and mental well-being. Based on the Scopus and Web of Science databases, the current study intends to analyse the global research output on machine learning in safety and health. This study utilized ScientoPy and VOSviewer to delve into the annual growth, patterns of research communication on source titles, international collaboration among countries, and authors' keyword analysis. This study found that the Web of Science database tracks the evolution of publications throughout time. PLoS One has surpassed all other source titles in terms of publishing activity. Also, this study indicated that US researchers are constantly working on machine learning in safety and health research and have developed significant collaborations with China and Australia. Between 2020 and 2021, the University of Toronto published 86% of all papers, outpacing other institutions. The keywords "machine learning", "artificial intelligence", "electronic health records", "deep learning", and "mental health" were the most popular and trending keywords in 2020 and 2021, and "artificial intelligence" appeared in most publications among others. Future researchers should conduct scoping or systematic literature reviews to elucidate the relationships between these terms. This study may entice the curiosity of practitioners and researchers to advance new knowledge in this field by being devoted to cutting-edge research in the contemporary philosophy of science, cognitive, and cultural anthropology on machine learning in safety and health research. In conclusion, this scientometric analysis demonstrates that machine learning in safety and health is a study domain that requires further refinement in future research, as this technology has the potential to significantly improve workplace safety and health through targeted applications with clear benefits. [ABSTRACT FROM AUTHOR]