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Newsweek Article Rating

Why the 2024 Election Shattered the Democratic Party | Opinion

Mar 19, 2025 View Original Article
  • Bias Rating

    40% Somewhat Conservative

  • Reliability

    65% ReliableAverage

  • Policy Leaning

    50% Medium Conservative

  • Politician Portrayal

    -59% Negative

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

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Bias Meter

Contributing sentiments towards policy:

55% : Stuart Gottlieb teaches international affairs and public policy at Columbia University.
49% : It is no coincidence that these states witnessed the largest shift toward Trump in the country in 2024 compared to 2020 (around 10 points each), helping him win the national vote by nearly 2.5 million.
48% : Democrats are understandably tempted to solve their current predicament in traditional fashion -- confront Trump with a new "resistance," tweak their policies and messaging, hope the 2026 midterms go their way.
43% : It turns out that even in the age of Trump, Americans of all stripes will vote not based on their racial or ethnic identity, but on which party they believe is better attuned to their overall needs and concerns.
41% : Trump 2024 exploded this myth by holding just five campaign rallies in three deep blue states typically ignored by Republican presidential nominees -- New Jersey (one), California (one), and New York (three).
36% : Professor of International and Public Affairs, Columbia University Since the 2024 election, the Democratic Party has been struggling to reconcile its significant losses, not just of the presidency and Senate majority, but of large swaths of formerly reliable Democratic voters.

*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.

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