Track global public opinion, political sentiment, and trust in government with insights from the 2025 Global Political Opinion Report.
Perception of Global Leaders - Nira Data
Discover global leader rankings, approval ratings, and reputation insights in the 2025 Perception of World Leaders report.
State Media Monitor Global Dataset 2025
This dataset provides comprehensive information on the governance, funding, and editorial independence of state and public media outlets worldwide. In 2025, the State Media Monitor covers 170 countries, tracking changes in media governance models, funding mechanisms, and degrees of political control. The dataset underpins the annual State Media Monitor Global Study and supports comparative research in journalism, media policy, and governance. Access the full dataset here: https://www.statemediamonitor.com
Nira Data – DPI Report
The Democracy Perception Index (DPI) is a cornerstone of the Copenhagen Democracy Summit, providing the most comprehensive global snapshot of public opinion on democracy.
Political polarization at its worst since the Civil War
Data scientists try to explain the U.S. government’s shifting ideologies over the past four decades.
Country Perception
How countries and global organizations are perceived around the world
Data Center Watch
Free weekly updates on the political risks facing American data center projects
World Monitor - Real-Time Global Intelligence Dashboard
Real-time global intelligence dashboard with live news, markets, military tracking, infrastructure monitoring, and geopolitical data. OSINT in one view.
The V-Dem Dataset – V-Dem
Includes the world's most comprehensive and detailed democracy ratings. The latest version of the dataset and associated reference documents can be downloaded free of charge below.
National Newswatch
National Newswatch: Canada's most comprehensive site for political news and views.
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.
Subscribe to Strength In Numbers
Independent, data-driven analysis of politics, public opinion polls, and elections. From author, journalist, and pollster G. Elliott Morris. Click to read Strength In Numbers, by G. Elliott Morris, a Substack publication with tens of thousands of subscribers.
Subscribe to Strength In Numbers
Independent, data-driven analysis of politics, public opinion polls, and elections. From author, journalist, and pollster G. Elliott Morris. Click to read Strength In Numbers, by G. Elliott Morris, a Substack publication with tens of thousands of subscribers.