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Nonverbal Behavioral Patterns Predict Social Rejection Elicited Aggression

机译:非语言行为模式预测社会拒绝引起的侵略

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Peer-based aggression following social rejection is a costly and prevalent problem for which existing treatments have had little success. This may be because aggression is a complex process influenced by current states of attention and arousal, which are difficult to measure on a moment to moment basis via self report. It is therefore crucial to identify nonverbal behavioral indices of attention and arousal that predict subsequent aggression. We used Support Vector Machines (SVMs) and eye gaze duration and pupillary response features, measured during positive and negative peer-based social interactions, to predict subsequent aggressive behavior towards those same peers. We found that eye gaze and pupillary reactivity not only predicted aggressive behavior, but performed better than models that included information about the participant's exposure to harsh parenting or trait aggression. Eye gaze and pupillary reactivity models also performed equally as well as those that included information about peer reputation (e.g. whether the peer was rejecting or accepting). This is the first study to decode nonverbal eye behavior during social interaction to predict social rejection-elicited aggression.
机译:社会拒绝后的基于同行的侵略是一种昂贵和普遍的问题,现有治疗成功。这可能是因为侵略是受当前关注和唤醒状态影响的复杂过程,这难以通过自我报告逐时衡量。因此,识别预测后续侵略的关注和唤醒的非语言行为指标至关重要。我们使用支持向量机(SVM)和眼睛凝视持续时间和瞳孔反应特征,在积极的同伴的社交互动期间测量,以预测随后对同一同龄人的攻击性行为。我们发现眼睛凝视和瞳孔反应性不仅预测了激进的行为,而且比包括有关参与者暴露于苛刻育儿或特征侵略的信息的模型更好。眼睛凝视和瞳孔反应性模型也同样进行,以及包括关于对等声名的信息(例如,对等体是否拒绝或接受)。这是第一次在社会互动期间解码非语言观察行为,以预测社会拒绝引发的侵略。

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