Yahoo News UK Article RatingNo Labels will not mount third-party 2024 bid after failing to find candidate
- Bias Rating
- Reliability
90% ReliableExcellent
- Policy Leaning
10% Center
- Politician Portrayal
-48% Negative
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
-15% Negative
- Liberal
- 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:
50% : " Biden v Trump: What's in store for the US and the world?14% : In 1992, the independent Ross Perot was widely held to have damaged George W Bush, the incumbent Republican president who lost to Bill Clinton.
13% : On the US left, Kennedy and No Labels have attracted widespread criticism for potentially damaging Biden in his rematch with Trump, though estimates vary over which candidate would stand to lose most voters to a serious third-party rival. Third-party candidates have swayed modern elections.
8% : " Biden and Trump do remain historically unpopular.
6% : In 2016 another Green, Jill Stein, performed strongly in key states lost by Hillary Clinton in her shock defeat by Trump.
*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.