Research Experiences
Research Assistant, AI & Society Research Group
Advisor: Dr. Pu Yan · May 2024 – Present
Contribute to two major funded projects bridging information science and social research.
- Assist the National Natural Science Foundation of China project “Influencing Factors and Mechanisms of the Algorithmic Divide” through literature reviews and quantitative data analysis.
- Support the Beijing Social Science Foundation project “Algorithm Literacy among Beijing Citizens” by refining survey instruments and conducting data modeling in R and Stata.
- Focus on algorithmic literacy, public trust, and social implications of AI systems in urban China.
Undergraduate Research Program
Project: Public Trust and Attitudes toward Generative AI in China
Advisor: Dr. Pu Yan · May 2024 – Oct 2025
Lead a multi-stage, mixed-methods study addressing the gap in localized AI trust measurement.
- Developed and validated a multi-dimensional GenAI Trust Scale through two large-scale surveys (N=662).
- Designed and executed a field experiment using Tobii eye-tracking to examine the causal effects of AI disclosure strategies on user trust.
- Conducted statistical analysis in R, identifying that simple AI labels enhance trust in conversational contexts but reduce it in news consumption.
- Extended this project in a cross-cultural study on Taiwanese public attitudes at National Tsing Hua University (Summer 2025, advised by Prof. Tzu-Hua Wang).
- This project forms the empirical foundation for future work on AI literacy and trust calibration across cultural contexts.
Peking University Challenge Cup Science Competition
Project: Rural Windows on Screens: Self-Presentation and Social Interaction of Middle-Aged and Elderly Women on Short-Video Platforms
Advisor: Dr. Xingkun Liang · Nov 2024 – Mar 2025
Result: First Prize, University Level · Presented at the 2025 Chinese Sociological Association Annual Conference
- Spearheaded a mixed-methods project integrating ethnographic fieldwork in rural Hebei with computational social science methods.
- Conducted 20+ semi-structured interviews and participant observation, exploring digital life among rural women.
- Independently scraped and analyzed comment data from Douyin and Kuaishou using Python (BERTopic) to model user interaction and self-presentation.
- Authored the final report framing short-video use as a flexible resistance to social marginalization and a tool for community building.
Empirical Research Project
Project: Alienation in Parent–Child Relationships Among Youth in the Context of Social Acceleration
Advisor: Dr. Xingkun Liang · Feb 2025 – June 2025
- Designed and conducted an empirical analysis using China Family Panel Studies (CFPS) data to investigate kin-estrangement.
- Applied OLS regression, mediation, and moderation models in Stata to examine how digital behaviors reshape family intimacy.
- Found that increased screen time significantly correlates with reduced parent–child closeness, offering insights into intergenerational alienation under digital acceleration.