The ethical dimensions of big data in refugee contexts: A scoping review of empirical studies in the social sciences

This scoping review examines the ethical dimensions of Big Data use as framed in empirical social science research on refugee protection and humanitarian response. It addresses the question: How are ethical issues conceptualized and addressed in empirical research on Big Data in refugee contexts? Following established scoping review frameworks, we systematically searched Web of Science, Scopus, Annual Reviews, and Google Scholar for peer-reviewed studies published between 2017 and 2025. Twenty-four studies met the inclusion criteria. Descriptive analysis shows that most research originates from Europe and North America, with limited contributions from refugee-hosting regions in the Global South. The reviewed studies used diverse data technologies—including social media analytics, remote sensing, machine learning, and mobile network data—to predict displacement, monitor mobility, and inform humanitarian decision-making. Thematic synthesis identified three recurring ethical tensions: (1) data-driven surveillance and refugee visibility, (2) predictive systems and algorithmic governance, and (3) humanitarian innovation and techno-solutionism. These findings reveal that while Big Data can enhance humanitarian action, it also reproduces structural inequalities and raises concerns around privacy, accountability, and refugee agency. The review concludes that ethical data practices in refugee governance must be participatory, transparent, and justice-oriented, balancing technological innovation with human rights and dignity.