New York Post Article RatingEx-FBI official Charles McGonigal accused of helping oligarch duck...
- Bias Rating
90% Extremely Conservative
- Reliability
50% ReliableFair
- Policy Leaning
N/A
- Politician Portrayal
56% 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
N/A
| Sentence | Sentiment | Bias |
|---|---|---|
| "A former top FBI agent in New York who investigated the Trump campaign's alleged ties to Russia in 2016 has been charged with money laundering and violating US sanctions for trying to help Russian oligarch Oleg Deripaska evade the penalties, the Justice Department said on Monday." | Negative | -24% Liberal |
| "McGonigal, who also served as the cyber-counterintelligence section chief in Washington, was one of the first FBI agents to learn that a Trump campaign official claimed that the Russians had dirt on then-Democratic presidential candidate Hillary Clinton, which triggered the investigation that continued into Donald Trump's presidency." | Negative | -8% Liberal |
| "McGonigal, who also served as the cyber-counterintelligence section chief in Washington, was one of the first FBI agents to learn that a Trump campaign official claimed that the Russians had dirt on then-Democratic presidential candidate Hillary Clinton, which triggered the investigation that continued into Donald Trump's presidency." | Negative | -8% Liberal |
| "McGonigal, who also served as the cyber-counterintelligence section chief in Washington, was one of the first FBI agents to learn that a Trump campaign official claimed that the Russians had dirt on then-Democratic presidential candidate Hillary Clinton, which triggered the investigation that continued into Donald Trump's presidency." | Negative | -8% Liberal |
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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.