Exploring conversation topics in conversational artificial intelligence–based social mediated communities of practice

• Published in: Computers in human behavior 2022-09, Vol.134, p.107326, Article 107326
• Main Authors: Ng, Yu-Leung, Lin, Zhihuai
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Communities of practice; Conversational AI; Latent dirichlet allocation; Uses and gratifications
• ISSN: 0747-5632; 1873-7692
• DOI: 10.1016/j.chb.2022.107326

This study utilized ecologically valid social media data to identify motivations and relevant topics regarding the interaction with conversational artificial intelligence (AI) in a natural setting through investigating user conversations on Reddit, a social mediated community of practice. By applying the latent Dirichlet allocation approach, this study extracted conversation topics in six subreddit communities among users of AI–powered virtual assistants (Apple Siri, Amazon Alexa, and Google Assistant) and the corresponding smart speakers (Apple HomePod, Amazon Echo, and Google Home), and investigated changes in the conversation topics over time. Findings showed six themes of conversation topics, i.e., functional gratification, hedonic gratification, social gratification, settings, problems encountered, and connections between devices. A large volatility of the conversation topics over time was found. The results implied that members in subreddit communities share their motivations for interacting with conversational AI and collaboratively discuss the relevant issues and problem solving to learn how to practice better. •This study adopted ecologically valid social media data to identify motivations and topics regarding conversational AI use.•Online members share their motivations (functional, hedonic, and social) for interacting with conversational AI.•Online members are collaborative learners who discuss issues and problem solving regarding conversational AI use.