Document Type

Conference Proceeding

Publication Date

2023

Keywords

Personal Health and Wellness Management with Technologies, artificial intelligence, conversational agents, design features, social chatbots, text mining

Abstract

Conversational agents are increasingly being used by the general population due to shortages in healthcare providers and specialists, and limited access to treatments. They are also used by people to deal with loneliness and lack of companionship. As these apps are increasingly replacing real humans, there is a need to explore their design features and limitations for better design of conversational apps. Using text mining and topic modeling, this study analyzed a total of 126,610 reviews about Replika, a popular and well-established conversational agent mobile app. Our results emphasized current practices for designing conversational apps while at the same time sheds the light on limitations associated with these apps. Such limitations are related to the need for better conversations and intelligent responses, the need for advanced AI chatbots, the need to avoid questionable and inappropriate content, the need for inclusive design, and the need to address some technical limitations.

Digital Object Identifier (DOI)

https://hdl.handle.net/10125/103023

Comments

Conference paper from:

Wahbeh, A., Al-Ramahi, M., El-Gayar, O., Elnoshokaty, A., & Nasralah, T. (2023). Conversational Agents for Mental Health and Well-being: Discovering Design Recommendations Using Text Mining. Proceedings of the 56th Hawaii International Conference on System Sciences.

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