A Bot and a Smile: Interpersonal Impressions of Chatbots and Humans Using Emoji in Computer-mediated Communication

TLDR

Artificially intelligent agents increasingly occupy roles once served by humans in computer‑mediated communication, and technological affordances such as emoji help overcome limited nonverbal information, yet few studies have examined how bots’ emoji use affects perceptions of communicator quality. The study investigates how emoji use influences observers’ perceptions of interpersonal attractiveness, CMC competence, and source credibility, and compares impressions of human versus chatbot message sources. The authors examined this relationship by analyzing observers’ ratings of emoji‑using versus verbal‑only message sources. Participants rated emoji‑using chatbot sources similarly to human sources, and both were judged more socially attractive, CMC competent, and credible than verbal‑only senders, a pattern interpreted through the CASA paradigm and the human‑to‑human interaction script framework.

Abstract

Artificially intelligent (AI) agents increasingly occupy roles once served by humans in computer-mediated communication (CMC). Technological affordances like emoji give interactants (humans or bots) the ability to partially overcome the limited nonverbal information in CMC. However, despite the growth of chatbots as conversational partners, few CMC and human-machine communication (HMC) studies have explored how bots’ use of emoji impact perceptions of communicator quality. This study examined the relationship between emoji use and observers’ impressions of interpersonal attractiveness, CMC competence, and source credibility; and whether impressions formed of human versus chatbot message sources were different. Results demonstrated that participants rated emoji-using chatbot message sources similarly to human message sources, and both humans and bots are significantly more socially attractive, CMC competent, and credible when compared to verbal-only message senders. Results are discussed with respect to the CASA paradigm and the human-to-human interaction script framework.