New York Post Article Rating- Bias Rating
-10% Center
- Reliability
55% ReliableFair
- Policy Leaning
N/A
- Politician Portrayal
98% Negative
Extremely
Liberal
Very
Liberal
Moderately
Liberal
Somewhat Liberal
Center
Somewhat Conservative
Moderately
Conservative
Very
Conservative
Extremely
Conservative
-100%
Liberal
100%
Conservative
Continue For Free
Create your free account to see the in-depth bias analytics and more.
Continue
Continue
By creating an account, you agree to our Terms and Privacy Policy, and subscribe to email updates. Already a member: Log inBias Score Analysis
The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.
Sentiments
N/A
| Sentence | Sentiment | Bias |
|---|---|---|
| "New York GOP Reps. Nick LaLota, Marc Molinaro and Brandon Williams are also cosponsoring the measure, which is a privileged resolution, meaning it must be voted on within two legislative days." | Positive | 8% Conservative |
| "New York GOP Reps. Nick LaLota, Marc Molinaro and Brandon Williams are also cosponsoring the measure, which is a privileged resolution, meaning it must be voted on within two legislative days." | Positive | 8% Conservative |
| "The Long Island pol was hit with 13 counts for the fibs and financial misdeeds in May -- and slapped with another 10 charges in October after his treasurer, Nancy Marks, admitted to lying on financial reports that Santos loaned his own campaign $500,000." | Negative | -8% Liberal |
Upgrade your account to obtain complete site access and more analytics below. | ||
Bias Meter
Extremely
Liberal
Very
Liberal
Moderately
Liberal
Somewhat Liberal
Center
Somewhat Conservative
Moderately
Conservative
Very
Conservative
Extremely
Conservative
-100%
Liberal
100%
Conservative
Contributing sentiments towards policy:
% :*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.