I have a life-time commitment to studying technology and democracy. Growing up in Taiwan, politics and identity were regular topics of conversation at the dinner table. Past projects include profiling bots that spread COVID-19 and election misinformation, and the role Instagram played in the Floyd Protests. My research has grown to applying machine learning and quantitative analysis to other social networks, including offshore finance and mentorship networks. I also helped invent an award-winning instrument.
My work has been featured in The Washington Post, the New York Times, Scientific American, and the Swiss National TV, and I collaborate with a few companies to better understand human behavior. For a full list of publications, please see my Google Scholar and press coverage in popular features.
Key themes: Inequality on social networks (racial, financial, and gender), misinformation, social algorithms
Chang & Fu
In mathematics, who you know matters. A network of 200,000 advisors and students show concerted efforts by academic committees, such as prize giving, can either reinforce the existing elite or reshape its definition.
Chang, Harrington, Fu, & Rockmore
Following the invasion of Ukraine, sanctions on oligarchs came under fire due to the oligarchs’ successful evasion. We analyze the role of an overlooked but highly influential group: the secretive professional intermediaries.
Chang, Richardson, & Ferrara
During the Floyd protests, positive framing emerged from unlikely opinion leaders: entertainment and meme accounts. Through 1.1 million photos, we show how content creators and citizen journalists shaped one of America's largest human rights movements.
Chang, Druckman, Ferrara, & Willer
Most Americans receive some political information through social media. Analyzing ten years of Twitter data (n=4 billion), we explore how liberals and conservatives engage with political information from elites.