Social touch is a rich channel of human communication, conveying emotion, intent, and meaning embedded in context. Yet most HCI studies treat touch in isolation, overlooking the layered subtleties that shape interpretation. We present a contextual analysis of 5,016 social touch events, grounded in a large collection of annotated scenes from films, dramas, and documentaries. Using a computer vision pipeline, we segmented touch events from video and annotated them across dimensions, including who is involved, how the gesture is performed, where on the body it occurs, and the cultural backdrop. Our analysis shows that identical gestures can convey distinct meanings depending on body location, relationship type, and context. Similar intentions—like comfort, encouragement, or dominance—may be expressed through different gestures or locations, shaped by relational dynamics, cultural norms, and public or private settings. These insights inform the design of socially aware touch technologies, including avatars, social agents, and mediated communication systems.
ACM CHI Conference on Human Factors in Computing Systems