Our Bias Meter detects and mitigates bias during your news consumption.

Biasly is a media bias rating agency that scans hundreds of articles daily to determine author bias and reliability issues within articles by using data science to analyze certain sentiments, policies, people, and terms found in the news.
Our proprietary algorithm (pending patent) uses deep neural network and natural language processing components that are trained to identify political sentiments in news articles and predict biases in real-time articles that we show on our website and newsletter. Through this process, a Computer Bias Score is created for each article.  Our site provides a list of bias scores and an overall average score for each news source including portrayals of politicians and policy leanings.
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How can I trust an A.I. machine learning system to tell me what is and isn’t biased?

Biasly’s diverse staff (ranging on all sides of the aisle) decide from a nonpartisan point of view, sentence by sentence, whether a certain excerpt has sentiment leaning and bias in it or is neutral.  

See bias analytics. Make better decisions.

Emphasizing reliability, we integrate the acuity of Biasly political analysts and the rigor of AI to generate a bias rating score for the most updated news articles.

01. AI-Powered Bias Detector

Bias Meter uses deep neural networks and natural language processing to identify political sentiments and predict biases in real-time news articles, generating a Computer Bias Score for each.
A bias meter shows a slight liberal bias at -6%. The evaluation includes sentiment (positive and negative) and portrayal bias. Source analysis is fair, opposite sources poor, multiple quotes excellent, and unique sources poor.

02. Biasly’s
Analysts

Our team of analysts rates articles from left, center, and right perspectives using Biasly’s proprietary methodology, providing a comparison mechanism to ensure and improve the accuracy of our computer-generated A.I. ratings.

Biasly’s Analyst Teams

Liberal

A blue dot centered within a light blue circular ring on a white background.
Supports social equality, and expansive government programs.

Moderate

A blue dot centered within a light blue circular ring on a white background.
Advocates balanced policies with more neutral leadings.

Conservative

A blue dot centered within a light blue circular ring on a white background.
Emphasizes tradition, limited goverment, and free-market principles.

Most updated AI analytics on most updated articles

At the beginning of every Biasly articles, you will see our bias and reliability scores which are provided in real-time, outside of the analyst scores.
A sentiment graph with data points 1 and 2 in red, indicating negative sentiment, and points 3 to 13 in blue, indicating neutral or slightly positive sentiment. Overall sentiment is 10% positive.

Sentiment analysis for most updated articles in news home.

AI Bias Score

Each Computer A.I. Bias Score includes the following analytics found on each article detail page. These ratings use the latest data science and A.I. analysis and neural networks to determine the scores.
Policy Leanings
Bias phrase and prediction
Politician portrayals
A circular diagram with five dark blue dots inside larger light blue circles, connected by a thin dark blue line.
Range of sentiment analysis
Opinion vs. Non-opinion Language

Source Analysis Score

Source Analysis Score includes the evaluation of the quality of sources and quotes used as outlined below。
Source diversity
Source quality
Formal vs. informal language
A circular diagram with five dark blue dots inside larger light blue circles, connected by a thin dark blue line.

Quote diversity

Quote quality

Screenshot showing performance ratings for various criteria: Analysis Score (Fair), Opposite Sources (Poor), Quote Length (Excellent), Unique Quotes (Poor), Unique Sources (Poor), and Multiple Sources (Fair).
Biasly’s Source Analysis Score categorically rate each articles from multifaceted perspectives.
A gauge displaying a spectrum from -100% Liberal (blue) to 100% Conservative (red). The needle points to the center, indicating a neutral position.
After combining all three scores, Bias Meter generates a composite score to reflect the objectivity of each article.

Fact Analysis reliability score

Our analysts manually assess the accuracy of facts and selection and omission bias presented in the article. It is equivalent to a fact-check. Our analysts are trained to research each article and determine the level of accuracy and selection and omission bias.

How can Biasly enhance your understanding of news?

Our Bias Meter is always improving to give readers the most accurate, factual information regarding their news sources. Biasly’s ability to process and fetch news for you, in real-time, with three different perspectives can provide insights about world events and political news and improve your media literacy.

Your personalized bias evaluator

Use Biasly surveys to understand your own biases.

Political Typology Survey

Evaluates your political personality type, offering several categories such as Democratic Socialist, Devoted Democrat, Core Conservative, Conservative Constitutionalist, and more. This feature provides a deeper understanding of the your political leanings.

Survey question asking how important it is for politicians to address climate control, with response options: Very Important, Somewhat Important, Neutral, Somewhat Unimportant, Very Unimportant.
A survey questionnaire with the title "What is Your Opinion on how the US Should Handle Gun Control?" It includes four response options with corresponding radio buttons for selection.

Personal Bias Survey

Provides a bias rating based on a linear scale from -36 to +36. Negative numbers denote liberal bias, while positive ones signify conservative bias, spanning seven distinct categories from Extremely Liberal to Extremely Conservative.
Feel free to continue learning about how ratings are derived by viewing our Political Party Conservative and Liberal Stances page

Biasly offers hands-on guidance for news analysis.