







We are the most comprehensive media bias resource on the internet. There are currently 3900+ media sources listed in our database and growing every day.
Ground News
The biggest source for breaking news around the world. Compare headlines across the political spectrum using media bias ratings driven by data.

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
Changes to the Facebook Algorithm Decreased News Visibility Between 2021-2024
Platforms, especially Facebook, are primary news sources in the US. In its widely criticized "War on News," Meta algorithmically deprioritized news and political content. We use data from 40 news organizations (5,243,302 Facebook posts, 7,875,372,958 user reactions) and 21 non-news pages (396,468 posts; 1,909,088,308 reactions) between January 1, 2016 and February 13, 2025 to examine how these changes influenced news visibility on the platform. Reactions to news declined by 78% between 2021 and 2024 while reactions to non-news pages increased, indicating targeted suppression of news visibility. Low-quality sources were especially suppressed, yet the 2025 end to "War on News" increased user reactions to news, especially low-quality ones. These changes do not reflect decreased news supply, Facebook user base, or interest in news over this period.

Media Influence Matrix – The World's Most Reliable Influence Tracker
This week’s edition reads five FY2025 reports against each other: Dnevnik (Slovenia), Delfi Latvia, Phoenix New Media (China), Hanza Media (Croatia) and Digi Communications (Romania). It finds two publishers separating their journalism from their balance sheets, a Croatian publisher closing a 35-year-old political weekly on a 1.1% net margin, a Chinese state-linked digital news group whose financial centre has quietly shifted from advertising to mini-program reading apps, and a Romanian telecom giant’s having its news channel walk off the must-carry list.
Who reposts which media sources? And why this matters for understanding populist politics
In social media, while documenting what gets said is important, understanding who posts which sources to raise their visibility is also key. Katharina Tittel, William Allen, and Pedro Ramaciotti use immigration in France to show how far-right users of X cite sources strategically to achieve their goals

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News Influencers Fact Sheet
About one-in-five U.S. adults say they regularly get news from news influencers on social media, and this is especially common among younger adults.

Wikipedia:Reliable sources/Perennial sources
This is a non-exhaustive list of sources whose reliability and use on Wikipedia are frequently discussed. This list summarizes prior consensus and consolidates links to the most in-depth and recent discussions from the reliable sources noticeboard and elsewhere on Wikipedia.
PropagandaScope
Tracking articles from newspapers. Real-time analysis of propaganda transmission patterns.
AI use in American newspapers is widespread, uneven, and rarely disclosed
AI is rapidly transforming journalism, but the extent of its use in published newspaper articles remains unclear. We address this gap by auditing a large-scale dataset of 186K articles from online editions of 1.5K American newspapers published in the summer of 2025. Using Pangram, a state-of-the-art AI detector, we discover that approximately 9% of newly-published articles are either partially or fully AI-generated. This AI use is unevenly distributed, appearing more frequently in smaller, local outlets, in specific topics such as weather and technology, and within certain ownership groups. We also analyze 45K opinion pieces from Washington Post, New York Times, and Wall Street Journal, finding that they are 6.4 times more likely to contain AI-generated content than news articles from the same publications, with many AI-flagged op-eds authored by prominent public figures. Despite this prevalence, we find that AI use is rarely disclosed: a manual audit of 100 AI-flagged articles found only five disclosures of AI use. Overall, our audit highlights the immediate need for greater transparency and updated editorial standards regarding the use of AI in journalism to maintain public trust.

AI use in American newspapers is widespread, uneven, and rarely disclosed
AI is rapidly transforming journalism, but the extent of its use in published newspaper articles remains unclear. We address this gap by auditing a large-scale dataset of 186K articles from online editions of 1.5K American newspapers published in the summer of 2025. Using Pangram, a state-of-the-art AI detector, we discover that approximately 9% of newly-published articles are either partially or fully AI-generated. This AI use is unevenly distributed, appearing more frequently in smaller, local outlets, in specific topics such as weather and technology, and within certain ownership groups. We also analyze 45K opinion pieces from Washington Post, New York Times, and Wall Street Journal, finding that they are 6.4 times more likely to contain AI-generated content than news articles from the same publications, with many AI-flagged op-eds authored by prominent public figures. Despite this prevalence, we find that AI use is rarely disclosed: a manual audit of 100 AI-flagged articles found only five disclosures of AI use. Overall, our audit highlights the immediate need for greater transparency and updated editorial standards regarding the use of AI in journalism to maintain public trust.

AMMeBa: A Large-Scale Survey and Dataset of Media-Based Misinformation In-The-Wild
The prevalence and harms of online misinformation is a perennial concern for internet platforms, institutions and society at large. Over time, information shared online has become more media-heavy and misinformation has readily adapted to these new modalities. The rise of generative AI-based tools, which provide widely-accessible methods for synthesizing realistic audio, images, video and human-like text, have amplified these concerns. Despite intense public interest and significant press coverage, quantitative information on the prevalence and modality of media-based misinformation remains scarce. Here, we present the results of a two-year study using human raters to annotate online media-based misinformation, mostly focusing on images, based on claims assessed in a large sample of publicly-accessible fact checks with the ClaimReview markup. We present an image typology, designed to capture aspects of the image and manipulation relevant to the image's role in the misinformation claim. We visualize the distribution of these types over time. We show the rise of generative AI-based content in misinformation claims, and that its commonality is a relatively recent phenomenon, occurring significantly after heavy press coverage. We also show "simple" methods dominated historically, particularly context manipulations, and continued to hold a majority as of the end of data collection in November 2023. The dataset, Annotated Misinformation, Media-Based (AMMeBa), is publicly-available, and we hope that these data will serve as both a means of evaluating mitigation methods in a realistic setting and as a first-of-its-kind census of the types and modalities of online misinformation.

AMMeBa: A Large-Scale Survey and Dataset of Media-Based Misinformation In-The-Wild
The prevalence and harms of online misinformation is a perennial concern for internet platforms, institutions and society at large. Over time, information shared online has become more media-heavy and misinformation has readily adapted to these new modalities. The rise of generative AI-based tools, which provide widely-accessible methods for synthesizing realistic audio, images, video and human-like text, have amplified these concerns. Despite intense public interest and significant press coverage, quantitative information on the prevalence and modality of media-based misinformation remains scarce. Here, we present the results of a two-year study using human raters to annotate online media-based misinformation, mostly focusing on images, based on claims assessed in a large sample of publicly-accessible fact checks with the ClaimReview markup. We present an image typology, designed to capture aspects of the image and manipulation relevant to the image's role in the misinformation claim. We visualize the distribution of these types over time. We show the rise of generative AI-based content in misinformation claims, and that its commonality is a relatively recent phenomenon, occurring significantly after heavy press coverage. We also show "simple" methods dominated historically, particularly context manipulations, and continued to hold a majority as of the end of data collection in November 2023. The dataset, Annotated Misinformation, Media-Based (AMMeBa), is publicly-available, and we hope that these data will serve as both a means of evaluating mitigation methods in a realistic setting and as a first-of-its-kind census of the types and modalities of online misinformation.

Amazing site here via @timnitgebru.bsky.social - a map of big tech influence on media and media companies. imo this goes a decent way to explaining why coverage of AI specifically has been so shockingly bad recently. Very useful resource!! nananwachukwu.github.io/media-capture-watch/
Doing some investigation into news data on atproto via @sill.social's appview. The most popular news orgs that don't have an account tied to their domain are: ABC, BBC, CBC. Broadcasting companies hate atproto, you heard it here first.
Majority of links are behind paywalls which I get; subscriptions in media are everywhere bc platforms killed distribution. How much traffic data actually translates to reading the article? I open links all the time and then close them bc of the paywall. We are reviving discovery but who’s reading?