ELDER ‐ MATCH : A Personality‐Aware Expert System for Elderly Social Connection Through AI ‐Powered Social Robots

ABSTRACT Global population aging has created unprecedented social isolation challenges among elderly populations, with significant negative health consequences. To address this, we propose ELDER‐MATCH, a personality‐aware expert system that moves beyond conventional interest‐ or need‐based matchmaking. By leveraging AI‐powered social robots as an interactive interface, our system helps elderly individuals form not just connections, but suitable and sustainable social relationships based on a deeper understanding of their personality and compatibility. We adopted a two‐stage framework: (1) a BERT‐based natural language processing stage deriving knowledge from conversational analysis to infer Big Five personality traits, and (2) a K‐means clustering stage employing a hybrid knowledge representation to identify compatible social connections based on weighted combinations of personality vectors, interests, and geographical constraints. The social robot provides an intuitive, accessible interface for knowledge acquisition and recommendation delivery, tailored specifically to elderly users with varying technological familiarity. The system was evaluated with 83 older adults across multiple community‐based settings. In Stage 2, our unsupervised learning approach identified seven distinct social compatibility clusters, each with specific reasoning rules guiding the recommendation engine. The expert system effectively facilitated meaningful social connections, with 76% of accepted recommendations resulting in ongoing relationships at the three‐month follow‐up. Beyond interests and needs, personality‐aware introductions reduce first‐meeting friction and improve trust calibration for older adults. We position ELDER‐MATCH as a mediator of human–human ties, and we articulate a “sunset‐by‐design” principle whereby the system fades as relationships stabilise. Longitudinal assessments revealed significant reductions in loneliness, expansion of participants' social networks, and notable improvements in psychological well‐being. These findings demonstrate that a two‐stage, personality‐aware expert system, coupled with a user‐centric interface, successfully bridges technological capabilities and social needs, advancing elderly social wellbeing through responsible AI application within the AI‐for‐Social‐Good paradigm. In practice, personality‐aware introductions reduce first‐meeting friction and calibrate trust for older adults—benefits that interest‐only systems rarely deliver in sustained relationships.