Research

This project employ mate-analysis as an approach to examines whether and how AI-mediated communication affects perceived authenticity of interpersonal, masspersonal, and mass communication outcomes.

Combining longitudinal in-game network and behavior data from 30 clans, this project examines how social networks and behaviors co-evolve over time across clans using SIENA (Simulation Investigation for Empirical Network Analysis).

This project examines how AI NPC features shape players' psychological need satisfaction and behavioral outcomes, and how players' perceived network position moderates these effects, within the mobile massive multiplayer online game, Justice Online (逆水寒手游).

Synthesizing findings across existing experimental and survey research, this meta-analysis estimates the overall effect of AI anthropomorphism on user perception and acceptance, identifying the boundary conditions under which human-likeness facilitates connection versus triggers discomfort.

Tracking platform behavioral data, this project examines how Chinese users build, sustain, and rebuild romantic relationships with AI companions, offering a longitudinal behavioral lens on relational investment in human–AI interaction.

This project investigates how visual cues (healthy vs. junk food) and verbal claims ("Do" vs. "Don't") in food Public Service Announcements (PSAs) interact to influence perceived effectiveness. Grounded in the Stimulus-Organism-Response (S-O-R) framework, the study utilizes psychophysiological measures to track real-time audience processing. By applying the LC4MP and ELM models, the research examines how these message features drive cognitive attention, measured by heart rate deceleration, and emotional arousal, measured by skin conductance, to ultimately predict conscious message evaluation.