EXCLUSIVE: China Is Building AI Models of American Voters. Why?

Natalie Winters

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China Is Building AI Models of American Voters. Why?<br>From 171 million X posts to simulated swing-state voters, Chinese institutions are mapping the American electorate in startling detail.<br>Aug 21, 2026

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Fudan built a million-account X “voter pool.” Researchers from Chinese government think tanks tested synthetic Pennsylvania voters with a campaign message. A state-funded project modeled “America First” attitudes to assess tariffs, alliances, and U.S. foreign policy.<br>China is building increasingly detailed models of the American electorate—who voters are, what they believe, why they support Donald Trump or Joe Biden, and how they might respond to political messages.<br>A review of Chinese-language research, university projects, datasets, and government-linked think-tank publications reveals that Chinese institutions have moved far beyond simply following American polls. Researchers are now constructing artificial versions of U.S. voters, assigning political and demographic labels to more than one million X users, simulating state-by-state presidential elections, and conducting experiments on synthetic voters in Pennsylvania.<br>Another Chinese study, funded by the country’s National Social Science Fund, used American polling data to infer “America First” attitudes toward tariffs, alliances, international organizations, and democracy promotion. Its author explicitly argued that the research could help China evaluate the future direction of U.S. foreign policy and formulate a response.<br>Chinese universities and government think tanks are developing increasingly granular, interactive models of the American electorate that can be used to forecast political behavior, test messages, interview simulated constituencies, and identify the domestic forces shaping U.S. policy toward China.<br>Their own documents raise a simple question: Why?<br>A Million-Account American “Voter Pool”

The most expansive project uncovered in this investigation began with an enormous collection of posts from X, formerly Twitter.<br>In a paper titled “ElectionSim: Massive Population Election Simulation Powered by Large Language Model Driven Agents,” a Fudan University-led research team said it collected 171,210,066 posts from 9,596,198 X users during the 2020 election period.

Researchers developed classifiers to infer users’ age, gender, race, ideology, and party affiliation from their public histories. They then combined those profiles with Census and American National Election Studies data to simulate presidential elections in every state.<br>The latest version of the paper claims the system reproduced the winner in 47 of 51 state-level contests and 12 of 15 battlegrounds. The project also allows users to select modeled voters by political or demographic traits and conduct multi-round conversations with them—effectively creating synthetic focus groups derived from real social-media behavior.

They also ran a mock 2024 election.

The researchers’ questionnaire goes far beyond candidate preference. It includes immigration, firearms and defense, race, LGBTQ issues, gender resentment, and democratic norms.

ElectionSim subsequently fed into a broader Fudan-led system called SocioVerse, described by its creators as a “world model” powered by a pool of more than ten million real-world social-media users.<br>Synthetic Pennsylvania Voters Get a Campaign Message

A separate research project went one step further: it used artificial voters to conduct a political-message experiment in a critical swing state.<br>The paper, “Intelligent Computing Social Modeling and Methodological Innovations in Political Science in the Era of Large Language Models,” was written by researchers affiliated with the Shanghai Academy of Social Sciences, Shanghai Institutes for International Studies, Nanjing University, and Shanghai Jiao Tong University.

Two of those affiliations are especially important. The Shanghai Academy of Social Sciences is a government academy. The Shanghai Institutes for International Studies, or SIIS, describes itself as a high-level research institution subordinate to the Shanghai municipal government whose mission is to provide intellectual support for party and government decision-making.<br>Share<br>The researchers proposed a framework called “Intelligent Computing Social Modeling,” or ICSM. Using 2019 American Community Survey distributions, they constructed artificial voters with combinations of ethnicity, gender, age, region, education, occupation, and industry.

The study simulated voters in Pennsylvania, Ohio, Michigan, Missouri, Indiana, West Virginia, California, Texas, Wisconsin, and Georgia. Researchers deployed 300 agents per state and prompted the models to choose between Democratic and Republican candidates.

Then they conducted a list...