How does the Electoral College work? A simple explanation for the 2024 presidential election
- Bias Rating
50% Medium Conservative
- Reliability
60% ReliableFair
- Policy Leaning
50% Medium Conservative
- Politician Portrayal
3% Positive
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
4% Positive
- 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:
19% : Trump is the GOP nominee again in the 2024 presidential election, in what's shaped up to be a tight race against Vice President Kamala Harris.15% : Trump lost both the popular vote and the Electoral College to Joe Biden in 2020.
8% : His opponent that year, Hillary Clinton, won over 2.8 million more votes than Trump nationwide, but she lost enough key states to be defeated in the Electoral College, 306 to 232.
*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.