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Paper Number

1379

Paper Type

short

Description

Live streaming has become increasingly popular in recent years for users to broadcast live events or experiences to an online audience in real-time. With the prevalence of the metaverse, virtual idols appear on the stage of live streaming. Unlike real human streamers, virtual idols are computer-generated avatars whose appearance does not exist in the physical world. Though existing literature has documented the effect of emotional displays of human streamers on viewers’ behavior, whether emotional displays of avatar streamers affect viewers’ behavior, especially viewers’ consumption behavior has not yet been explored. To fill this gap, we focus on the live streaming of virtual idols and conduct deep learning approaches to investigate the emotional synchrony between avatar streamers and their viewers based on moment-to-moment data. Our analysis of large-scale video data shows that the larger the discrepancy between the streamers’ acoustic- and text- emotions, the more likely the viewers will pay. This study sheds light on how avatars can be designed to leverage emotion to engage viewers in more consumption.

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Dec 11th, 12:00 AM

Emotional Synchrony and Viewers’ Consumption: Evidence from Live Streaming of Virtual Idols

Live streaming has become increasingly popular in recent years for users to broadcast live events or experiences to an online audience in real-time. With the prevalence of the metaverse, virtual idols appear on the stage of live streaming. Unlike real human streamers, virtual idols are computer-generated avatars whose appearance does not exist in the physical world. Though existing literature has documented the effect of emotional displays of human streamers on viewers’ behavior, whether emotional displays of avatar streamers affect viewers’ behavior, especially viewers’ consumption behavior has not yet been explored. To fill this gap, we focus on the live streaming of virtual idols and conduct deep learning approaches to investigate the emotional synchrony between avatar streamers and their viewers based on moment-to-moment data. Our analysis of large-scale video data shows that the larger the discrepancy between the streamers’ acoustic- and text- emotions, the more likely the viewers will pay. This study sheds light on how avatars can be designed to leverage emotion to engage viewers in more consumption.

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