"I Am in Your Computer While We Talk to Each Other" a Content Analysis on the Use of Language-Based Strategies by Humans and a Social Chatbot in Initial Human-Chatbot Interactions

This research analyses the use of language-based strategies in human-chatbot interactions, namely the use of self-disclosure, question asking, expressions of similarity, empathy, humour, and the communication competence of the chatbot. This study aims to discover whether humans and a social chatbot communicate differently. Furthermore, we analyzed to what extent the chatbot's expressions affect the human users' expressions. A content analysis was conducted based on previously collected data from a longitudinal study, in which participants interacted seven times with chatbot Mitsuku over the course of three weeks. A randomly selected sample of 60 interactions was coded and results revealed that the participants self-disclosed more (intimately) and used more reciprocal self-disclosures, while the chatbot asked more questions, more reciprocal questions and more follow-up questions, expressed more similarity and humour. Moreover, the more questions the chatbot asked, the more the participants reciprocated these questions, and the more they self-disclosed. Our findings show that chatbots are programmed to gather information, by asking questions, to keep the conversation going, which elicits self-disclosure in human users. However, the self-disclosure was not reciprocated, which may hinder human-chatbot relationship formation.