The National Article RatingYour Party unveils name shortlist ahead of conference
- Bias Rating
- Reliability
45% ReliableAverage
- Policy Leaning
6% Center
- Politician Portrayal
N/A
Continue For Free
Create your free account to see the in-depth bias analytics and more.
By creating an account, you agree to our Terms and Privacy Policy, and subscribe to email updates.
Bias 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
32% Positive
- 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:
52% : More than 2500 members have been selected to attend the event, where supporters will also consider whether the party should back "socialist" independent candidates at the May 2026 local elections.48% : " But she also took aim at a decision by the outfit, so far referred to as Your Party, to kick out members who also held membership to the Socialist Workers Party.
47% : Asked whether she would reinstate the membership of those who had been kicked out, and why she thought the expulsions had happened, Sultana said: "Yes. "I think there is a culture of paranoia at the very top, where disagreements are seen as existential, and when you have a movement that is seeking to unite the left, bringing socialists of every stripe in, you have to allow people to be able to organise." She said the party should avoid "witch hunts" and a "toxic" culture that does not unify the left.
*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.
