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      Effects of Persuasive Dialogues: Testing Bot Identities and Inquiry Strategies

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          Abstract

          Intelligent conversational agents, or chatbots, can take on various identities and are increasingly engaging in more human-centered conversations with persuasive goals. However, little is known about how identities and inquiry strategies influence the conversation's effectiveness. We conducted an online study involving 790 participants to be persuaded by a chatbot for charity donation. We designed a two by four factorial experiment (two chatbot identities and four inquiry strategies) where participants were randomly assigned to different conditions. Findings showed that the perceived identity of the chatbot had significant effects on the persuasion outcome (i.e., donation) and interpersonal perceptions (i.e., competence, confidence, warmth, and sincerity). Further, we identified interaction effects among perceived identities and inquiry strategies. We discuss the findings for theoretical and practical implications for developing ethical and effective persuasive chatbots. Our published data, codes, and analyses serve as the first step towards building competent ethical persuasive chatbots.

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          Author and article information

          Journal
          13 January 2020
          Article
          10.1145/3313831.3376843
          2001.04564
          234f8990-1d10-453a-8478-db02c68756dc

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          Custom metadata
          15 pages, 10 figures. Full paper to appear at ACM CHI 2020
          cs.HC

          Human-computer-interaction
          Human-computer-interaction

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