Journal Article

Two-Layer Panopticon: How the Chinese Government Uses Digital Surveillance to Prevent Collective Action

Joint Text-and-Image Clustering for Social Science Research

Hug Fans or Follow Celebrities? How Nationalism Is Reinforced on Chinese Social Media

Patriarchal Erasure and Manufactured Passivity: Asymmetric Government and News Media Attention to Protests in China

Underrepresentation and Misrepresentation: Selection and Description Bias in Protest Reporting by Government and News Media on Weibo

Robots and Protest: Does Increased Protest Among Chinese Workers Result in More Automation?

Image Clustering: An Unsupervised Approach to Categorize Visual Data in Social Science Research

How Using Machine Learning Classification as a Variable in Regression Leads to Attenuation Bias and What to Do About It

Abstract: Social scientists have increasingly been applying machine learning algorithms to “big data” to measure theoretical concepts they cannot easily measure before, and then …

Authoritarian Responsiveness and Political Attitudes during COVID-19: Evidence from Weibo and a Survey Experiment

CASM: A Deep Learning Approach for Identifying Collective Action Events with Text and Image Data from Social Media

NOTE: There are three great invited commentaries to our article by Zachary C. Steinert-Threlkeld, Swen Hutter, and Pamela Oliver. Read them and our response here.

Addressing Selection Bias in Event Studies with General-Purpose Social Media Panels