Unveiling the Impact of Multi-Modal Interactions on User Engagement: A Comprehensive Evaluation in AI-driven Conversations

• URL: http://arxiv.org/abs/2406.15000v1
• Date: Fri, 21 Jun 2024 09:26:55 GMT
• Title: Unveiling the Impact of Multi-Modal Interactions on User Engagement: A Comprehensive Evaluation in AI-driven Conversations
• Authors: Lichao Zhang, Jia Yu, Shuai Zhang, Long Li, Yangyang Zhong, Guanbao Liang, Yuming Yan, Qing Ma, Fangsheng Weng, Fayu Pan, Jing Li, Renjun Xu, Zhenzhong Lan,
• Abstract summary: This paper explores the impact of multi-modal interactions, which incorporate images and audio alongside text, on user engagement. Our findings reveal a significant enhancement in user engagement with multi-modal interactions compared to text-only dialogues. Results suggest that multi-modal interactions optimize cognitive processing and facilitate richer information comprehension.
• Score: 17.409790984399052
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Large Language Models (LLMs) have significantly advanced user-bot interactions, enabling more complex and coherent dialogues. However, the prevalent text-only modality might not fully exploit the potential for effective user engagement. This paper explores the impact of multi-modal interactions, which incorporate images and audio alongside text, on user engagement in chatbot conversations. We conduct a comprehensive analysis using a diverse set of chatbots and real-user interaction data, employing metrics such as retention rate and conversation length to evaluate user engagement. Our findings reveal a significant enhancement in user engagement with multi-modal interactions compared to text-only dialogues. Notably, the incorporation of a third modality significantly amplifies engagement beyond the benefits observed with just two modalities. These results suggest that multi-modal interactions optimize cognitive processing and facilitate richer information comprehension. This study underscores the importance of multi-modality in chatbot design, offering valuable insights for creating more engaging and immersive AI communication experiences and informing the broader AI community about the benefits of multi-modal interactions in enhancing user engagement.

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