Artificial intelligence-powered chatbots capable of expressing emotions have gained significant popularity in the realm of customer service. Although previous studies have explored the impact of emotional expression in chatbots, there is a lack of understanding regarding the precise effects of different emotional cues. In this study, we drew upon social presence theory to investigate how different emotional cues conveyed by recommendation chatbots affect perceived humanness, social interactivity, and social presence. We conducted a series of scenario-based online experiments to shed light on these dynamics. We found that all three emotional cues (text, emoticons, and images) employed by chatbots can increase perceived humanness and social interactivity. Social presence appears to be an underlying mechanism for these positive relationships. We also observed two-way interactions for any pair of emotional cues and a three-way interaction for all three emotional cues. Ultimately, to elicit the most favorable customer perception, we propose that a mode of emotional expression using either text or emoticons alone is most appropriate. These findings deepen our understanding of the impact of emotional expressions in chatbots and offer novel insights into how to deploy chatbots in customer service.

中文翻译：

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人工智能推荐聊天机器人的情感表达对感知人性和社会互动性的影响


能够表达情感的人工智能聊天机器人在客户服务领域广受欢迎。尽管以前的研究已经探讨了聊天机器人中情绪表达的影响，但对不同情绪线索的确切效果缺乏了解。在这项研究中，我们借鉴了社交存在理论来研究推荐聊天机器人传达的不同情感线索如何影响感知到的人性、社交互动和社会存在。我们进行了一系列基于情景的在线实验，以阐明这些动态。我们发现，聊天机器人使用的所有三种情感线索（文本、表情符号和图像）都可以增加感知到的人性和社会互动性。社会存在似乎是这些积极关系的潜在机制。我们还观察到任何一对情绪线索的双向交互和所有三种情绪线索的三向交互。最终，为了获得最有利的客户感知，我们建议单独使用文本或表情符号的情感表达模式是最合适的。这些发现加深了我们对聊天机器人中情绪表达影响的理解，并为如何在客户服务中部署聊天机器人提供了新的见解。