Verbal Mimicry Predicts Social Distance and Social Attraction to an Outgroup Member in Virtual Reality

Salvador Alvídrez, Jorge Peña
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引用次数: 1

Abstract

The present study analyzes the extent to which verbal mimicry contributes to improving outgroup perceptions in virtual reality (VR) interactions. Particularly, this study examined the interplay between avatar customization, the salience of a common ingroup identity, and verbal mimicry in 54 VR dyads comprising users from different ethnic backgrounds. Participants were asked to customize their avatars to look either like themselves or someone completely different. Participants interacted wearing either similar avatar uniforms (salient common identity) or different clothes (nonsalient identity). The linguistic style matching (LSM) algorithm was employed to calculate verbal mimicry in the communication exchanged during a joint task. The results suggested that verbal mimicry significantly predicted lesser social distance and greater social attraction towards the outgroup member. These results are discussed in terms of their contribution for potential intergroup models of avatar communication in immersive virtual environments (IVEs).
虚拟现实中言语模仿预测外群体成员的社会距离和社会吸引力
本研究分析了言语模仿在虚拟现实(VR)互动中有助于改善外群体感知的程度。特别地,这项研究在54个由不同种族背景的用户组成的虚拟现实组合中检验了虚拟形象定制、共同群体内身份的显著性和语言模仿之间的相互作用。参与者被要求定制他们的头像,要么看起来像自己,要么看起来完全不同。参与者要么穿着相似的虚拟角色制服(突出的共同身份),要么穿着不同的衣服(不突出的身份)进行互动。采用语言风格匹配(LSM)算法计算联合任务中交流中的言语模仿。结果表明,言语模仿显著地预示着更小的社会距离和对外群体成员更大的社会吸引力。这些结果对沉浸式虚拟环境(IVEs)中虚拟角色通信的潜在群体间模型的贡献进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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