2024 in review: A look back at the election through Tribune op-eds
- Bias Rating
16% Somewhat Conservative
- Reliability
30% ReliableFair
- Policy Leaning
54% Medium Conservative
- Politician Portrayal
-2% 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
18% Positive
- Liberal
- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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Contributing sentiments towards policy:
66% : Social media evolution: Trump has adapted his visual communication style to new formats, favoring short, punchy video clips and memes.61% : Today's delegates are chosen, most of them, as a reward for their loyalty to the Democratic Party and the strength of their personal and political connections to the winner of the primaries.
47% : J. Marcos Peterson, "I am a Mexican American who voted for Trump.
43% : What motivated traditional Democratic voting blocs to turn out for Trump?
42% : From the infrastructure bill that Trump promised and couldn't deliver, to the largest investment ever in funding to combat climate change, Biden signed laws that helped veterans, promoted gun safety, lowered the cost of prescription drugs, and boosted clean energy jobs and manufacturing of computer chips back on American soil.
27% : Donald Trump is going to be our nation's next president, but how he got there and how the Democrats lost are a journey worth revisiting.
22% : As Trump and his cohorts might say: Boring.Oct. 2: Laura Washington, "Here's what Harris must do to appeal to a fractured voter base"If Kamala Harris wants to broaden her base, she must attract voters seeking a conservative message.
20% : Voting for Donald Trump does not make me racist, sexist, misogynistic, homophobic or any other "ist" and "ic" I've been called.
*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.