Kuhail, MA, Thomas, J, Alramlawi, S, Shah, SJH and Thornquist, E (2022) Interacting with a Chatbot-Based Advising System: Understanding the Effect of Chatbot Personality and User Gender on Behavior. Informatics, 9 (4).
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Abstract
Chatbots with personality have been shown to affect engagement and user subjective satisfaction. Yet, the design of most chatbots focuses on functionality and accuracy rather than an interpersonal communication style. Existing studies on personality-imbued chatbots have mostly assessed the effect of chatbot personality on user preference and satisfaction. However, the influence of chatbot personality on behavioral qualities, such as users’ trust, engagement, and perceived authenticity of the chatbots, is largely unexplored. To bridge this gap, this study contributes: (1) A detailed design of a personality-imbued chatbot used in academic advising. (2) Empirical findings of an experiment with students who interacted with three different versions of the chatbot. Each version, vetted by psychology experts, represents one of the three dominant traits, agreeableness, conscientiousness, and extraversion. The experiment focused on the effect of chatbot personality on trust, authenticity, engagement, and intention to use the chatbot. Furthermore, we assessed whether gender plays a role in students’ perception of the personality-imbued chatbots. Our findings show a positive impact of chatbot personality on perceived chatbot authenticity and intended engagement, while student gender does not play a significant role in the students’ perception of chatbots.
Item Type: | Article |
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Uncontrolled Keywords: | 0806 Information Systems; 0807 Library and Information Studies |
Subjects: | B Philosophy. Psychology. Religion > BF Psychology Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
Divisions: | Psychology (from Sep 2019) |
Publisher: | MDPI AG |
SWORD Depositor: | A Symplectic |
Date Deposited: | 26 May 2023 11:45 |
Last Modified: | 26 May 2023 11:45 |
DOI or ID number: | 10.3390/informatics9040081 |
URI: | https://researchonline.ljmu.ac.uk/id/eprint/19585 |
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