Machine Learning in Recruitment: Key Research Themes and Future directions

Abstract

The paper provides a thorough bibliometric analysis of 150 research articles published between 2007 and 2023, particularly emphasising the use of machine learning in recruiting. The research examines publishing trends, well-known periodicals, and noteworthy contributors, including writers, institutions, and nations. The results provide insightful information for researchers, assisting in choosing reputable journals for publishing and summarising the main research subjects and growing subfields. The use of machine learning in emerging recruiting fields, including bias reduction, diversity and inclusion, ethical considerations, and privacy issues, should be explored in future research paths. Further research is also advised on how machine learning may be combined with other cutting-edge technologies, such as natural language processing and collective decision-making techniques. Machine learning techniques may improve the recruitment function, resulting in more effective and efficient talent acquisition tactics.

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