Effects of Persuasive Dialogues: Testing Bot Identities and Inquiry Strategies

要旨

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.

キーワード
Empirical study that tells us about people
Text/Speech/Language
Behavior Change
Crowdsourced
著者
Weiyan Shi
University of California, Davis, Davis, CA, USA
Xuewei Wang
Carnegie Mellon University, Pittsburgh, PA, USA
Yoo Jung Oh
University of California, Davis, Davis, CA, USA
Jingwen Zhang
University of California, Davis, Davis, CA, USA
Saurav Sahay
Intel Labs, Santa Clara, CA, USA
Zhou Yu
University of California, Davis, Davis, CA, USA
DOI

10.1145/3313831.3376843

論文URL

https://doi.org/10.1145/3313831.3376843

会議: CHI 2020

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)

セッション: In dialogue with AI

Paper session
316C MAUI
5 件の発表
2020-04-29 01:00:00
2020-04-29 02:15:00
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