Insights into Digital Identity Dynamics through Personal Digital Twins

Abstract

The digital transformation has resulted in a web of complex systems, creating a tangled mesh of context-specific digital identities for users to manage. Despite the prevalence of privacy risks, users often remain unaware of the extent to which their personal data is used by identity providers and relying parties. Drawing on design science and network analysis techniques, this paper introduces a hierarchical node architecture and data flow model to highlight the interconnectedness of partial digital identities and provides a tool to support the assessment and evaluation process. We used the developed methods to evaluate the digital footprint of ten participants, gaining insights into digital identity dynamics.