Minzu University of China · Haidian, Beijing

Theo Zhou周璜达

Computational Social Science · Public Policy · Artificial Intelligence

I am interested in the intersection of artificial intelligence, computational methods, and the social sciences, with a particular focus on computational social science, public policy, digital governance, and data-driven social research. I hope to use data, models, and computational tools to better understand real-world social and policy problems and explore the evolving relationship between technology and society.

Email
zhoudada86@gmail.com
Illustrated avatar of Theo Zhou
AI × Computational Methods × Social Science

Selected Research

Research grounded in real-world evidence

From nationwide government social media data to city-level policy evaluation, I use computational and econometric methods to study public communication, interaction, and policy effects.

Conference Paper · First Author

Government Expression & Public Interaction on Social Media

Using 328,544 posts from 337 verified government Weibo accounts, this study combines NLP, machine learning, and panel-data methods to examine how government communication strategies relate to public interaction.

Computational Social ScienceNLPMachine LearningPanel Data
337Verified accounts
328,544Original posts
Working Paper · Collaborative Research · Submitted to Chinese Public Administration · Under external review

Can City Branding Improve the Business Environment?

Using the National Sanitary City designation as a quasi-natural experiment, this study applies staggered difference-in-differences (staggered DID) to a 2004–2021 city panel to evaluate business-environment effects.

Policy EvaluationDIDCSDIDCausal Inference
5,177City-year observations
2004–2021Study period

Featured Project

WeiboFish reorganizes real government social media data, empirical metrics, semantic retrieval, and multi-agent simulation into an interactive research prototype.

Research Prototype · 2026

WeiboFish

From empirical social science to multi-agent simulation.

An interactive research prototype built from 328,544 real-world government social media posts, NLP models, semantic retrieval, and multi-agent simulation.

AI AgentsRAGNLPSimulationComputational Social Science
  • 328,544 real-world posts
  • 337 government accounts
  • 1,000 heterogeneous agents

Recent / Conference

Chinese Sociological Association Annual Conference 2026

The paper was selected for a thematic forum on social transformation in the digital-intelligence era, with a written presentation and poster session.

Xi'an, China · July 2026Chinese Sociological Association Annual Conference

Experience

Real-world experience beyond research

From household field surveys to data validation and analytical drafting, this experience showed me how social data are produced, verified, and interpreted in practice.

Meeting room during the Liuyang Survey Team internship

Survey & Office AssistantJun. 2025 — Sep. 2025

Liuyang Survey Team, National Bureau of Statistics of China

Completed five rounds of household field visits, follow-up verification, and Excel-based data processing, and led the analysis and first draft of one internally released city/county analytical brief.

5Field survey rounds
10+Households per round
ExcelValidation & analysis
View full experience →

About

Connecting technical methods with social questions

I am an undergraduate student at Minzu University of China, majoring in Public Service Management and pursuing a micro-major in Intelligent Management and Business Data Analytics. My interests lie at the intersection of artificial intelligence, computational methods, and the social sciences.

My academic and field experiences connect public administration, computational methods, and real-world social questions.

About me →