A BIBLIOMETRIC ANALYSIS OF GLOBAL RESEARCH ON DATA USE IN SOCIAL SERVICES (1950–2026): EVIDENCE FROM THE WEB OF SCIENCE DATABASE USING VOSVIEWER

Mohammed A. Alkohaiz Kholud S. Makkawi

This study investigates the global scholarly production on the use of data in social services using a bibliometric approach based on the Web of Science database. In the context of rapid digital transformation and the increasing integration of data-driven approaches in social work, there is a growing need to systematically map and analyze the intellectual structure and evolution of this interdisciplinary field. The study aims to (1) identify the most scientifically productive countries in the field of data use in social services, (2) analyze the temporal evolution of scientific production, (3) explore the intellectual structure and research clusters, and (4) identify emerging future research directions in the field. A total of (512) publications were retrieved and analyzed using VOSviewer to perform co-occurrence, network, and visualization analyses, in order to identify the knowledge structure of scientific production in the field of data use for improving social services. The results show that China, the United States, and the United Kingdom are the leading contributors in terms of scientific productivity. Temporal analysis revealed four developmental stages in the evolution of research on data use in social services, with a marked acceleration in scientific output between 2020 and 2026. The intellectual structure of the field was organized into five major clusters, focusing on data privacy and security, advanced analytics techniques, data mining and social networks, big data and machine learning applications, and social media–driven data analytics. Emerging research directions include computational social science, socio-technical imaginaries, digital twins, the Social Internet of Things (SIoT), social genomics, and Social Representation Theory. The study concludes that data-driven approaches are increasingly reshaping social services and social work practice, highlighting the need for stronger interdisciplinary collaboration and capacity-building in data analytics within the social sector