Foundations, Present, and Future of the Algorithmic Regulation Domain. A Holistic Bibliometric Analysis

Algorithmic regulation is a novel topic that has gained relevance in recent years. However, there is a lack of comprehensive studies with a systematic approach using bibliometric, data-driven quantitative techniques to understand the structure of knowledge and collaboration in this field. This paper aims to address this gap through bibliometric quantitative methods supported by machine learning tools. Scopus and Web of Science (WoS) databases were consulted, and after data selection and cleaning, 354 documents were quantitatively assessed to unveil the foundations, current state, and future directions of this topic. The foundations are characterized by two complementary approaches (critical and inquisitive). The present is defined by six main schools of thought focused on six key themes: ethics, human resources, artificial intelligence, blockchain, algorithmic governance, and technology. The future is shaped by growing concerns regarding artificial intelligence and algorithmic governance as broad and evolving topics.