ABC30 News Article RatingRepublicans expected to retake the House with razor-thin majority: What this could mean
- Bias Rating
-2% Center
- Reliability
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- Policy Leaning
-14% Somewhat Liberal
- Politician Portrayal
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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
| Sentence | Sentiment | Bias |
|---|---|---|
| "But last week's election results indicate that McCarthy would instead have to lead with few, if any, votes to spare on those priorities from a fractious conference made up of competing viewpoints from moderates, pro-Trump representatives, fiscal conservatives and more." | Positive | 0% Conservative |
| "Anticipating a return to power, McCarthy had unveiled a Commitment to America while promising to focus on immigration at the southern border, cutting funding to the IRS, reassessing U.S. support for Ukraine and investigating the Biden White House." | Negative | -12% Liberal |
| "She previously suggested to The New York Times that to be the best speaker of the House and to please the base, [McCarthy is] going to give me a lot of power." | Positive | 22% Conservative |
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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Contributing sentiments towards policy:
50% : But last week's election results indicate that McCarthy would instead have to lead with few, if any, votes to spare on those priorities from a fractious conference made up of competing viewpoints from moderates, pro-Trump representatives, fiscal conservatives and more.44% : Anticipating a return to power, McCarthy had unveiled a "Commitment to America" while promising to focus on immigration at the southern border, cutting funding to the IRS, reassessing U.S. support for Ukraine and investigating the Biden White House.
*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.