🤖 AI Summary
This study investigates the timing, placement, and emotion-regulatory function of smiles in Holocaust survivors’ trauma narratives. By developing a high-accuracy facial feature recognition model (F1 = 85%) and integrating multimodal analyses of audio, eye-tracking, and textual data, the research systematically examines the relationship between smiling behavior and narrative structure, semantic themes, and emotional trajectories. Analysis of video testimonies from 978 survivors reveals that smiles occur significantly within negatively valenced contexts, where they not only enhance local emotional valence but also modulate ocular dynamics and blink frequency. These findings provide the first empirical evidence of an adaptive emotion-regulation mechanism through smiling during the recollection of extreme trauma.
📝 Abstract
We study when, where, and why 978 Holocaust survivors smile in video testimonies. We create an automatic smile detection model from facial features with an F1 of 85% and annotate detected smiles under two established taxonomies of smiling. We produce narrative features on 1,083,417 transcript sentences as well as emotional valence from three different modalities: audio, eye gaze, and text transcript. Smiling rates are significantly correlated with specific semantic topics, narrative structures, and temporal syntaxes across the entire corpus. Smiles often occur during periods of intense negative affect; these negative-affect smiles improve the valence trajectory of surrounding sentences significantly across all three modalities. Smiling reduces eye dynamics and blink rates, and the strength of both of these effects is also modulated by narrative valence. Taken together, we conclude that smiling plays a critical role in regulating emotion and social interaction during traumatic recollection.