Give us our flats! The angry victims of China's property crisis
- Bias Rating
42% Medium Conservative
- Reliability
40% ReliableFair
- Policy Leaning
42% Medium 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
- 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:
57% : China's largest city has a sophisticated court system, with some of the country's best lawyers and judges who are well versed in commercial law.43% : They are in good company: a group of dissident netizens began collecting data on boycotts across China in June 2022, revealing that tens of thousands of people had stopped paying as a form of protest.
41% : Just months after he bought his flat, the Chinese government introduced a raft of policies designed to cool an overheating property market.
32% : The only channel for talks has been at the lowest level of government, a "petition office" close to One Riviera where local residents can complain about everything from noisy neighbours to small-scale corruption.
*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.