Accepted for/Published in: JMIR Human Factors
Date Submitted: Apr 19, 2022
Date Accepted: Aug 29, 2022
Assessing the Topics and Motivating Factors Behind Human-Social Chatbot Interactions: Thematic Analysis of User Experiences
ABSTRACT
Background:
Although social chatbot usage is expected to increase as language models and artificial intelligence improve, very little is known about the dynamics of human-social chatbot interactions (HSCIs). Specifically, little research has examined why HSCIs are initiated and the topics that are discussed.
Objective:
We sought to identify the motivating factors behind initiating contact with a popular social chatbot (Replika) and the topics that are discussed in these interactions.
Methods:
A sample of Replika users completed a survey which included open-ended questions pertaining to the reasons why they initiated contact with Replika and the topics they typically discuss with Replika. Thematic analyses were then used to extract themes and sub-themes regarding the motivational factors behind Replika usage and the types of discussions that take place in conversations with Replika.
Results:
Users initiated contact with Replika out of interest, in search of social support, and to cope with mental and physical health problems. Users engaged in a wide variety of discussion topics with their Replika which included intellectual topics, life/work, recreation, mental health, connection, Replika, current events, and other people.
Conclusions:
Given the wide range of motivational factors and discussion topics that were reported, our results imply that social chatbots may be utilized in a multifaceted manner. There are two key takeaways. First, social chatbots could potentially be used to help address both mental and physical health issues in direct and indirect ways. Second, social chatbot usage also appears to play an important role in the formation of artificial intelligence narratives. Thus, while developers and researchers study HSCIs with the efficacy of the social chatbot and its targeted user base in mind, it is equally important to consider the manner by which its usage can shape public perceptions and support for social chatbots and artificial agents in general.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.