
Put the Debate Champagne Away, Democrats. Trump Can Still Beat Harris
- Bias Rating
- Reliability
40% ReliableAverage
- Policy Leaning
50% Medium Right
- Politician Portrayal
-36% Negative
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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
-16% Negative
- Liberal
- Conservative
Sentence | Sentiment | Bias |
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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-100%
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100%
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Contributing sentiments towards policy:
71% : Three hours later, Trump declared victory.50% : If he doesn't, she wins by the tacit admission from Trump that he knows he can't beat her one-on-one.
42% : Trump still maintains the edge as the candidate voters prefer on three of the most important issues in the election: the economy, immigration and the Middle East.
38% : In order to win on Tuesday night (and possibly in November), Trump needed to demonstrate discipline and focus, proving to the country that the Vice President is what he has made her out to be: weak, incompetent and dangerously liberal-a task he failed at in spectacular fashion.
37% : That pattern suggests that Harris needs to outperform Trump nationally by at least three to four points in order to ensure a win on election night -- and she is not there yet.
35% : It's hard to overstate the stakes of this election for Trump.
29% : This race isn't over till it's over -- even if Trump jumped the shark.
27% : And in the first thirty minutes, Trump fought like a guy who-literally-has his life on the line.
7% : In the same CNN poll taken immediately after the first general election debate between Trump and Clinton in 2016, Trump actually fared worse with only 24% of respondents declaring him the winner.
*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.