Ph.D. Candidate | Hong Kong Baptist University

Yingying Fan

AI Governance, Emergency Management, and Computational Social Science.

I am a Ph.D. candidate in the Department of Government and International Studies at Hong Kong Baptist University.

My research focuses on AI governance, public policy, and emergency management, with particular attention to how digital technologies are transforming public-sector governance, policy implementation, and crisis response.

Methodologically, I use natural language processing, social network analysis, multimodal analysis, and geospatial analysis to study governance and policy problems. I am also developing AI agents and computational tools for social science research.

Publications and current work

Doctoral dissertation

Algorithmic Friction: How AI Reshapes Administrative Burden in China’s Street-Level Bureaucracy

This project examines how AI-mediated public administration changes administrative burden, frontline discretion, and the relationship between citizens and public institutions.

Working paper

Not All Formal Arrangements Persist Across Crisis Phases

Command and coordination in Macao’s civil protection response.

Working paper

Concept Measurement in the Age of Large Language Models

Theory-based coding in multimodal short-video data.

Computational work

Open Source Tools for Social Science Research

My methodological toolkit includes natural language processing, social network analysis, LLM-assisted coding, data visualization, and geospatial analysis.

More tools and research code are available here.

research_stack = {
  questions: ["AI governance", "emergency management"],
  methods: ["SNA", "NLP", "AI-agent-assisted analysis", "GIS"],
  tools: ["Python", "R", "Gephi", "ArcGIS"]
}

LDA Research Workflow

A reproducible topic-modeling workflow for text-as-data research in computational social science.