Afghan refugees are starting to arrive in Utah. Here's what you need to know.
- Bias Rating
-4% Center
- Reliability
N/AN/A
- Policy Leaning
-2% Center
- Politician Portrayal
70% Negative
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Liberal
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Moderately
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Center
Somewhat Conservative
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Conservative
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Extremely
Conservative
-100%
Liberal
100%
Conservative
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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
N/A
- Liberal
Sentence | Sentiment | Bias |
---|---|---|
"Arshad Salem used to work in a human resources office at the United Nations, close to the U.S. Army and consultants." | Positive | 2% Conservative |
"Biden has reversed that, and Utah is once again poised to take in 1,200 refugees." | Negative | -20% Liberal |
"At their peak, they helped roughly 1,200 refugees a year, but that was before former President Donald Trump drastically reduced the number allowed in the country." | Negative | -24% Liberal |
"Utah Gov. Spencer Cox sent President Joe Biden a letter shortly after the Taliban swept into Kabul and forced the chaotic exit of the U.S. military and many Afghans." | Negative | -4% Liberal |
"Utah Gov. Spencer Cox sent President Joe Biden a letter shortly after the Taliban swept into Kabul and forced the chaotic exit of the U.S. military and many Afghans." | Negative | -4% Liberal |
Bias Meter
Extremely
Liberal
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Liberal
Moderately
Liberal
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Center
Somewhat Conservative
Moderately
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Very
Conservative
Extremely
Conservative
-100%
Liberal
100%
Conservative
Contributing sentiments towards policy:
51% : Arshad Salem used to work in a human resources office at the United Nations, close to the U.S. Army and consultants.*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.