Human similarity judgments reveal fine-grained representations of dynamic social scenes
Year: 2026
Type: preprint
Abstract: How does the human mind organize dynamic social scenes? Existing accounts rely on pre-defined social-affective or action-based taxonomies, yet whether humans use these dimensions to structure their representations of naturalistic social scenes remains unknown. We collected 53,223 human similarity judgments of videos depicting two-person actions and trained a sparse-positive-embedding model to recover the underlying latent dimensions. These learned dimensions explained twice as much variance in similarity judgments as pre-labeled annotations, captured interpretable fine-grained social-event structure (combining information about social relationships and actions), and fractionated broad semantic content (e.g., separating parent-child interactions into caregiving versus affectionate play). The same dimensions also predicted fMRI responses to passively viewed stimuli across visual cortex better than pre-labeled annotations, highlighting their importance beyond similarity judgments. Together, these results suggest that humans represent dynamic social scenes along fine-grained axes not captured by current taxonomies, and offer behaviorally-grounded targets for future studies of social vision.
Source: PsyArXiv (OSF Preprints)
Authors: Kathy Garcia, Leyla Isik
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7223325127