Although users’ expectations of a chatbot’s performance could greatly shape their interaction experience, they have been underexplored in the context of social support where chatbots are gaining popularity. A 2 × 2 experiment created expectancy violation and confirmation conditions by matching or mismatching a chatbot’s expertise label (expert vs. non-expert) and its interactional contingency (contingent vs. generic feedback to users). Contingent feedback from chatbots was found to have positive effects on participants’ evaluation of the bot and their perceived emotional validation, regardless of the bot’s expertise label. When providing generic feedback to participants, a bot received worse evaluation and induced less emotional validation on participants when it was labeled as an expert, rather than a non-expert, highlighting the detrimental effect of negative expectancy violation than negative expectancy confirmation in interactions with a social support chatbot.
The study features a lab experiment which created conditions that positively or negatively violated users' expectations of a chatbot.
