Enhancing user experience with conversational agent for movie recommendation: Effects of self-disclosure and reciprocity

By Seoyoung Lee, Junho H. Choi. Int. J. Hum. Comput. Stud., 2017

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Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale (2022, background): “However, we must mention that digital literacy is not a substitute for AI literacy in HAII research.”
Towards Designing Cooperative and Social Conversational Agents for Customer Service (2017, background): “Consequently, researchers in HCI have studied how users react to humanlike characteristics of CAs (e.g., Ochs et al. 2017) and how these characteristics affect their behavior (e.g., Lee and Choi 2017).”
"I Hear You, I Feel You": Encouraging Deep Self-disclosure through a Chatbot (2020, methodology): “Three constructs - trust [13], intimacy [4], and enjoyment [31, 46] - were measured through the same survey twice: after the first and third week of using the chatbot.”
How Should My Chatbot Interact? A Survey on Social Characteristics in Human–Chatbot Interaction Design (2019, background): “[S3] reciprocity and self-disclosure: [Lee and Choi 2017] hypothesized that a high level of self-disclosure and reciprocity in communication with chatbots would increase trust, intimacy, and enjoyment, ultimately improving user satisfaction and intention to use.”
A Survey on Conversational Recommender Systems (2020, background): “, by increasing the user’s trust and developing intimacy [70], or by adapting the communication style (e.”