Harris dismisses Trump as the 'same old show' as he rips into her on race
- Bias Rating
10% Center
- Reliability
65% ReliableFair
- Policy Leaning
10% Center
- Politician Portrayal
-9% Negative
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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
-13% Negative
- Liberal
- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
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Contributing sentiments towards policy:
73% : In the arena before Trump spoke, an old headline displayed on a megatron read: "California's Kamala Harris becomes the first Indian American US senator."67% : "Trump ticked through much of the primaries and then the early phases of the general election under the careful watch of a more professionalized campaign, with fewer of the off-message moments that became the hallmark of his 2016 and 2020 campaigns.
53% : "And back in Harrisburg, Trump himself acknowledged a kind of reversion had taken place.
36% : "There were other signs on Wednesday that Trump was channeling the darker vestiges of 2016.
32% : And if Trump had opened a wound, his campaign seemed intent on pressing a thumb deeper into it.
32% : Harris, speaking in Texas as Trump was finishing his remarks, didn't take the bait.
30% : During an interview at a convention of Black journalists in Chicago earlier Wednesday, Trump had tried to boost his profile with Black voters by arguing that immigrants coming to the country illegally were taking over "Black jobs" and "taking employment away from Black people."
24% : At a rally in Harrisburg, Pennsylvania, Trump focused his remarks on "crazy Kamala's policies."
10% : But while Trump did not repeat his suggestion at the rally that Harris only recently "became" Black -- he posted on social media that Harris was a "stone cold phony."
*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.