Exclusive: Internal U.N. document says Taliban threatened, beat staff
- Bias Rating
80% Very Conservative
- Reliability
N/AN/A
- Policy Leaning
80% Very Conservative
- Politician Portrayal
N/A
Continue For Free
Create your free account to see the in-depth bias analytics and more.
Continue
Continue
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
- Conservative
Sentence | Sentiment | Bias |
---|---|---|
Unlock this feature by upgrading to the Pro plan. |
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
Contributing sentiments towards policy:
49% : A second Afghan woman who works at the United Nations has been moving houses with her husband and 3-year-old daughter in the past 10 days.48% : The United Nations has relocated about a third of the 300 foreign staff it had in Afghanistan to Kazakhstan.
44% : Some of her neighbors knew she worked at the United Nations, and she worried they might inform on her.
41% : She has a visa for a neighboring country, but is frustrated that the United Nations has not helped her evacuate.
40% : The United Nations said it did not comment on leaked security documents.
39% : He said the threats were not all necessarily linked to people's status at the United Nations, but were a function of the Taliban's push to impose control over Kabul.
35% : An Afghan woman, who has worked for the United Nations for several years, told Reuters she felt abandoned.
*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.