Tacit Understanding Game (TUG): Predicting Interpersonal Compatibility

Abstract

Research on relationship quality often relies on lengthy questionnaires or invasive textual corpora, limiting ecological validity and user privacy. We ask whether a sequence of single-word choices made in a playful setting can reveal personality and predict interpersonal compatibility. We introduce the Tacit Understanding Game (TUG), a two-player online word association game. We collect word choice traces, annotate a subset with psychological ground truth scales, and bootstrap a larger synthetic corpus via large language model simulation. TUG demonstrates that minimal, privacy preserving signals can support relationship matching, offering new design space for social platforms.