New York Post Article RatingNYC Council hates cops and just put yet another nail in the city's...
- Bias Rating
22% Somewhat Conservative
- Reliability
55% ReliableFair
- Policy Leaning
6% Center
- Politician Portrayal
46% Negative
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-100%
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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
-6% Negative
- Conservative
| Sentence | Sentiment | Bias |
|---|---|---|
| "Officers in such encounters can ask non-accusatory questions such as Where are you going? and can request identification, but the civilian involved is free to leave." | Negative | -2% Liberal |
| "He writes: Because Iran and its proxies have so many weapons stocked all over the region, it will take some time until Biden, Secretary of Defense Austin and Secretary of State Blinken can find an empty warehouse to attack." | Negative | -10% Liberal |
| "Reader Paula Tay asks the gazillion-dollar question, writing: Many of Donald Trump's policies were sound and beneficial." | Positive | 10% Conservative |
| "He writes: Because Iran and its proxies have so many weapons stocked all over the region, it will take some time until Biden, Secretary of Defense Austin and Secretary of State Blinken can find an empty warehouse to attack." | Negative | -14% Liberal |
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Bias Meter
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Contributing sentiments towards policy:
49% : Officers in such encounters can ask non-accusatory questions such as "Where are you going?" and can request identification, but the civilian involved is free to leave.45% : He writes: "Because Iran and its proxies have so many weapons stocked all over the region, it will take some time until Biden, Secretary of Defense Austin and Secretary of State Blinken can find an empty warehouse to attack.
*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.