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Enhancing Reflective and Conversational User Engagement in Argumentative Dialogues with Virtual Agents.

Authors :
Aicher, Annalena
Matsuda, Yuki
Yasumoto, Keichii
Minker, Wolfgang
André, Elisabeth
Ultes, Stefan
Source :
Multimodal Technologies & Interaction; Aug2024, Vol. 8 Issue 8, p71, 44p
Publication Year :
2024

Abstract

In their process of information seeking, human users tend to selectively ignore information that contradicts their pre-existing beliefs or opinions. These so-called "self-imposed filter bubbles" (SFBs) pose a significant challenge for argumentative conversational agents aiming to facilitate critical, unbiased opinion formation on controversial topics. With the ultimate goal of developing a system that helps users break their self-imposed filter bubbles (SFBs), this paper aims to investigate the role of co-speech gestures, specifically examining how these gestures significantly contribute to achieving this objective. This paper extends current research by examining methods to engage users in cooperative discussions with a virtual human-like agent, encouraging a deep reflection on arguments to disrupt SFBs. Specifically, we investigate the agent's non-verbal behavior in the form of co-speech gestures. We analyze whether co-speech gestures, depending on the conveyed information, enhance motivation, and thus conversational user engagement, thereby encouraging users to consider information that could potentially disrupt their SFBs. The findings of a laboratory study with 56 participants highlight the importance of non-verbal agent behaviors, such as co-speech gestures, in improving users' perceptions of the interaction and the conveyed content. This effect is particularly notable when the content aims to challenge the user's SFB. Therefore, this research offers valuable insights into enhancing user engagement in the design of multimodal interactions with future cooperative argumentative virtual agents. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
24144088
Volume :
8
Issue :
8
Database :
Complementary Index
Journal :
Multimodal Technologies & Interaction
Publication Type :
Academic Journal
Accession number :
179379795
Full Text :
https://doi.org/10.3390/mti8080071