Peter Navarro, who authored 2020 election irregularities report, sentenced to four months in prison
- Bias Rating
-4% Center
- Reliability
55% ReliableFair
- Policy Leaning
44% Medium Conservative
- Politician Portrayal
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-100%
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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
-16% Negative
- Liberal
- Conservative
Sentence | Sentiment | Bias |
---|---|---|
"In a Facebook post of Dec. 19, 2020, Trump praised the report, compiled with the assistance of Navarro's deputy Garrett Ziegler." | Positive | 66% Conservative |
"Peter Navarro releases 36-page report alleging election fraud 'more than sufficient' to swing victory to Trump -- A great report by Peter." | Positive | 30% Conservative |
"Navarro said at Thursday's sentencing hearing that he defied the subpoena because he believed in good faith that Trump had invoked executive privilege." | Positive | 18% Conservative |
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Bias Meter
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Contributing sentiments towards policy:
83% : In a Facebook post of Dec. 19, 2020, Trump praised the report, compiled with the assistance of Navarro's deputy Garrett Ziegler.65% : "Peter Navarro releases 36-page report alleging election fraud 'more than sufficient' to swing victory to Trump -- A great report by Peter.
59% : Navarro said at Thursday's sentencing hearing that he defied the subpoena because he believed in "good faith" that Trump had invoked executive privilege.
43% : Nobody in my position should be put in conflict between the legislative branch and the executive branch.
5% : "Attorney Lin Wood posted on Telegram about lawfare against Trump and his attorneys and supporters:Have you noticed that ALL the criminal charges against President Trump (which started after the 8/8/022 illegal raid on Mar-a-Lago) have been factually and legally baseless???
*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.