Author

Date of Award

2026

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Psychology

Committee Chair

Jodi Price

Committee Member

Daniel Krenn

Committee Member

Yizhou Liu

Committee Member

Ryan Weber

Committee Member

Wafa Orman

Research Advisor

Jodi Price

Subject(s)

Cognitive psychology, Human-computer interaction, Machine learning, Artificial intelligence, Social intelligence, Trust

Abstract

This dissertation investigates how users form perceptions of social intelligence and trust when interacting with large language model chatbots. Three experimental studies manipulated chatbot agreeableness, goal orientation, and simulated short-term memory, measuring perceived social intelligence and trust. The primary finding is an asymmetric effect of personality: disagreeable chatbot behavior produced large reductions in perceived social intelligence and trust, whereas agreeable behavior produced negligible gains above a warm baseline, consistent with negativity bias in social cognition. Goal orientation did not independently enhance perceptions but functioned as a contextual moderator. Simulated memory produced medium-to-large increases in perceived social intelligence without reliably increasing trust, indicating that personalized social knowledge and trustworthiness engage partially distinct pathways. Individual differences in gender, prior experience with artificial intelligence, and perceived chatbot humanness consistently moderated experimental effects. Results carry implications for the design of socially intelligent artificial intelligence systems.

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