A Trust Construction Model in Human-AI Social Interactions: A Dual-Path Analysis Based on Algorithmic Transparency and Emojis

Main Article Content

Yunjun Han
LUC/BJTU Weihai Campus, Beijing Jiaotong University, Weihai, Shandong, China, 264401, China

DOI: https://doi.org/10.70267/ic-aimees.202512

Keywords

social AI, user trust, AI trust, social presence, algorithmic transparency, emojis

Abstract

In the context of the rapid development of social AI applications today, user trust has become a crucial prerequisite for their long-term adoption, yet the mechanisms underlying its formation still lack systematic research from an emotional perspective. To address this, this study proposes a dual-path model based on “algorithmic transparency and emojis,” introducing social presence as a mediating variable to explore its influence mechanism on user trust. Employing empirical methods for research and analysis, the results demonstrate that both algorithmic transparency and emoji usage can significantly enhance users’ trust in social AI, with social presence playing a mediating role between algorithmic transparency, emoji usage, and user trust. The findings of this study not only expand the theoretical perspectives on trust construction in social AI but also offer practical suggestions for algorithmic transparency design and interaction optimization.

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Published
Dec 19, 2025
Conference Proceedings Volume
Vol. 9 (2025): Proceedings of the 2025 International Conference on Artificial Intelligence, Modern Engineering and Environmental Sustainability (IC-AIMEES 2025)
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How to Cite

Han, Yunjun. “A Trust Construction Model in Human-AI Social Interactions: A Dual-Path Analysis Based on Algorithmic Transparency and Emojis”. Exploring Science Academic Conference Series, vol. 9, Dec. 2025, pp. 92-107, https://doi.org/10.70267/ic-aimees.202512.

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