Persuasion in Pixels and Prose: The Effects of Emotional Language and Visuals in Agent Conversations on Decision-Making

要旨

The growing sophistication of Large Language Models allows conversational agents (CAs) to engage users in increasingly personalized and targeted conversations. While users may vary in their receptiveness to CA persuasion, stylistic elements and agent personalities can be adjusted on the fly. Combined with image generation models that create context-specific realistic visuals, CAs have the potential to influence user behavior and decision making. We investigate the effects of linguistic and visual elements used by CAs on user perception and decision making in a charitable donation context with an online experiment (n=344). We find that while CA attitude influenced trust, it did not affect donation behavior. Visual primes played no role in shaping trust, though their absence resulted in higher donations and situational empathy. Perceptions of competence and situational empathy were potential predictors of donation amounts. We discuss the complex interplay of user and CA characteristics and the fine line between benign behavior signaling and manipulation.

著者
Hüseyin Uğur Genç
TU Delft, Delft, Netherlands
Senthil Chandrasegaran
TU Delft, Delft, Netherlands
Tilman Dingler
Delft University of Technology, Delft, Netherlands
Himanshu Verma
TU Delft, Delft, Netherlands
DOI

10.1145/3706598.3713579

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713579

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Decision Making and Analysis

G414+G415
6 件の発表
2025-04-30 20:10:00
2025-04-30 21:40:00
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