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

Yu Leung NG*, Zhihuai LIN

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Article number107326
Number of pages17
JournalComputers in Human Behavior
Volume134
DOIs
Publication statusPublished - Sep 2022

Scopus Subject Areas

  • Psychology(all)
  • Arts and Humanities (miscellaneous)
  • Human-Computer Interaction

User-Defined Keywords

  • Artificial intelligence
  • Communities of practice
  • Conversational AI
  • Latent dirichlet allocation
  • Uses and gratifications

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