Abstract
This work explores the effect of chatbot personality on user experience and investigates how users perceive agent personality when conveyed through text. Building on previous work in the field of human-computer interaction on designing chatbot personality, we investigate whether users in a low-stakes conversation have a preference for a specific personality type when the agent does not use voice, is not visually represented, and does not provide identity cues such as gender. We developed two chatbots that interact with users in a multi-turn conversation and designed them to have distinct personalities along two axes of the Five Factor Model (extraversion and agreeableness). We conducted a user study to evaluate user engagement, user perception of the agents, and the effect of user personality on user experience.
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Notes
- 1.
Mitsuku: https://www.pandorabots.com/mitsuku/.
- 2.
Beauty recommendation chatbots: https://beauty.bot/directory/makeup/.
- 3.
CNN Chatbot: https://marutitech.com/news-made-personal-with-chatbots/.
- 4.
Weather chatbots: https://chatbottle.co/bots/messenger/weather.
- 5.
Woebot: https://woebothealth.com/.
- 6.
Microsoft Bot Framework: https://dev.botframework.com.
- 7.
- 8.
The bots were called Makoto and Nasoto. Makoto is an ungendered Japanese name, and Nasoto is a non-word. These names are culturally distant from the cultural background of our sample and thus unlikely to be readily associated with a specific gender, age-group, or other identity.
- 9.
Natural Language Toolkit: https://www.nltk.org/.
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Acknowledgements
This work was supported, in part, by Science Foundation Ireland grant 13/RC/2094. Thank you to Dr. Brendan Rooney and Dr. Nicola Fox Hamilton for their very helpful advice. Thank you to Thomas Laurent and Glynda Ruane for their useful feedback on an earlier version of this manuscript.
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Ruane, E., Farrell, S., Ventresque, A. (2021). User Perception of Text-Based Chatbot Personality. In: Følstad, A., et al. Chatbot Research and Design. CONVERSATIONS 2020. Lecture Notes in Computer Science(), vol 12604. Springer, Cham. https://doi.org/10.1007/978-3-030-68288-0_3
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