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Paper Type

ERF

Abstract

Chatbots that use generative artificial intelligence to reply have become an important application in the field of human-AI interaction and also related to a new diversity of virtual communities. There is a lack of study for composition factors and patterns of quasi-social interaction in the process of human-chatbot interaction. We propose a new model with a hybrid approach, aiming to explore the mechanism of interactive ritual in human-AI interaction using interactive ritual chain theory. This research aims to answer the quasi-social interaction between humans and chatbots, in order to deeply study the mechanism of human society and psychology. In addition, this study will also adopt quantitative research methods to verify the impact and effectiveness of interactive rituals on users' willingness to use chatbots. Through this research, we aim to provide guidance for designing smarter and more user-friendly AI systems, thereby facilitating the development and improvement of human-AI interaction.

Paper Number

1484

Author Connect URL

https://authorconnect.aisnet.org/conferences/AMCIS2024/papers/1484

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Aug 16th, 12:00 AM

Understanding Users' Response to Chatbots from the Perspective of Interactive Ritual Chain

Chatbots that use generative artificial intelligence to reply have become an important application in the field of human-AI interaction and also related to a new diversity of virtual communities. There is a lack of study for composition factors and patterns of quasi-social interaction in the process of human-chatbot interaction. We propose a new model with a hybrid approach, aiming to explore the mechanism of interactive ritual in human-AI interaction using interactive ritual chain theory. This research aims to answer the quasi-social interaction between humans and chatbots, in order to deeply study the mechanism of human society and psychology. In addition, this study will also adopt quantitative research methods to verify the impact and effectiveness of interactive rituals on users' willingness to use chatbots. Through this research, we aim to provide guidance for designing smarter and more user-friendly AI systems, thereby facilitating the development and improvement of human-AI interaction.

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