Shared Similarity Between Humans and Chatbots: Exploring Human Willingness to Seek Social Support From Chatbots
Zicheng Zhu, Tianqi Song, Jefferson Lim, Chi-Lan Yang, Yi-Chieh Lee
Abstract
Despite the importance of social support in mental health, people often lack access to it. Chatbots have emerged as an alternative approach to providing social support, yet people demonstrate reluctance to embrace this approach. Drawing on social identity theory, we examine how shared similarities between people and chatbots—particularly in attitude, personality, and experience —influence people’s willingness to seek social support from chatbots. We conducted three experiments (N = 205), each focusing on one dimension of similarity. Our results showed that participants were more willing to seek social support from chatbots with similar attitudes and experiences and that displayed extroversion. Furthermore, similarity in attitude boosted participants’ willingness to seek support from chatbots by enhancing their closeness with chatbots, and similarity in experience increased it by improving both closeness and perceived chatbots’ ability to offer support. Implications for designing chatbots for social support are discussed.
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