How a Chinese marketing network quietly injects political narratives into Taiwanese lifestyle content

A new investigation by Reporters Without Borders (RSF) reveals how certain Facebook pages posing as lifestyle hubs for hobbies and health tips inject Beijing’s political narratives into their feeds to influence public opinion in Taiwan. These pages are tied to the China-based digital marketing company Wubianjie, which blends entertainment, disinformation and political messaging in cognitive warfare campaigns that are difficult to detect.

Vatnik Soup on Twitter / X

In China, social media influencers often livestream in wealthy neighborhoods to increase the chances of attracting the attention of affluent and influential viewers. pic.twitter.com/GKz7RiAHcS— Vatnik Soup (@P_Kallioniemi) July 26, 2026

Yuntian Deng on Twitter / X

Claude has become a language, so I built a translator.English <-> Claudish pic.twitter.com/871CI2XdUz— Yuntian Deng (@yuntiandeng) August 22, 2026

Frased.com on Instagram: "Asians do it better #quoteoftheday #funnyshirt #girlfriend #asian #inlove"

5,620 likes, 96 comments - frased.unfiltered on April 27, 2026: "Asians do it better #quoteoftheday #funnyshirt #girlfriend #asian #inlove".

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State media control influences large language models

Millions of people around the world query large language models (LLMs) for information. Although several studies have compellingly documented the persuasive potential of these models1–10, there is limited evidence of who or what influences the models themselves, leading to a flurry of concerns about which companies and governments build and regulate the models. Here we show through six studies that government control of the media across the world already influences the output of LLMs via their training data. We use a cross-national audit to show that LLMs exhibit a stronger pro-government valence in the languages of countries with lower media freedom than in those with higher media freedom. This result is correlational, so to triangulate the specific mechanism of how state media control can influence LLMs, we develop a multi-part case study on China’s media. We demonstrate that media scripted and curated by the Chinese state appears in LLM training datasets. To evaluate the plausible effect of this inclusion, we use an open-weight model to show that additional pretraining on Chinese state-coordinated media generates more positive answers to prompts about Chinese political institutions and leaders. We link this phenomenon to commercial models through two audit studies demonstrating that prompting models in Chinese generates more positive responses about China’s institutions and leaders than do the same queries in English. The combination of influence and persuasive potential across languages suggests the troubling conclusion that states and powerful institutions have increased strategic incentives to leverage media control in the hopes of shaping LLM output.

State media control influences large language models

Millions of people around the world query large language models (LLMs) for information. Although several studies have compellingly documented the persuasive potential of these models1–10, there is limited evidence of who or what influences the models themselves, leading to a flurry of concerns about which companies and governments build and regulate the models. Here we show through six studies that government control of the media across the world already influences the output of LLMs via their training data. We use a cross-national audit to show that LLMs exhibit a stronger pro-government valence in the languages of countries with lower media freedom than in those with higher media freedom. This result is correlational, so to triangulate the specific mechanism of how state media control can influence LLMs, we develop a multi-part case study on China’s media. We demonstrate that media scripted and curated by the Chinese state appears in LLM training datasets. To evaluate the plausible effect of this inclusion, we use an open-weight model to show that additional pretraining on Chinese state-coordinated media generates more positive answers to prompts about Chinese political institutions and leaders. We link this phenomenon to commercial models through two audit studies demonstrating that prompting models in Chinese generates more positive responses about China’s institutions and leaders than do the same queries in English. The combination of influence and persuasive potential across languages suggests the troubling conclusion that states and powerful institutions have increased strategic incentives to leverage media control in the hopes of shaping LLM output.

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