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Trump Looks to Block Key Witnesses at Hush Money Trial
- Bias Rating
- Reliability
40% ReliableAverage
- Policy Leaning
86% Very Right
- Politician Portrayal
-72% Negative
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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
Overall Sentiment
-47% Negative
- Conservative
| Sentence | Sentiment | Bias |
|---|---|---|
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
Extremely
Liberal
Very
Liberal
Moderately
Liberal
Somewhat Liberal
Center
Somewhat Conservative
Moderately
Conservative
Very
Conservative
Extremely
Conservative
-100%
Liberal
100%
Conservative
Somewhat Right
34%
Contributing sentiments towards policy:
29% : The motion goes after witness credibility, noting that Cohen has already perjured himself, and Daniels, aka Stephanie Clifford, "intends to offer false, salacious, and unduly prejudicial testimony relating to President Trump.14% : Trump has been accused of falsifying business records to conceal the payments.
4% : The Trump hush money case centers on allegations that Trump had his then-lawyer Cohen make payments to Daniels and McDougal on the condition they refrain from discussing affairs which Trump has denied.
*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.
Check out this free eBook to learn more about detecting misinformation in the news.