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New York Post Article Rating

Democrats’ premature victory lap, old Leninism in a new suit and other commentary

  • Bias Rating
  • Reliability

    65% ReliableAverage

  • Policy Leaning

    -10% Center

  • Politician Portrayal

    -56% 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

Overall Sentiment

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Bias Meter

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Bias Meter

Contributing sentiments towards policy:

56% : Refugees from socialism see Zohran Mamdani as “an immediately recognizable type,” a representative of an “educated vanguard” who “teaches effortless insincerity as a necessary means to reaching power.”
53% : But New York City’s embrace of “socialism lite” has already eroded “its economic base,” with most net job growth “traced to the hiring of home health aides.”
40% : ICE is allowed to stop “people simply based upon their race or their language or accent,” and it’s “not exactly shocking if a lot of” Latino voters feel they “run a much higher risk of needing to prove their American citizenship.”
38% : Democratic Socialism’s rise portends “nothing good,” because “this version [of leftism] is even dumber” than its predecessors, having “remade itself” based on “a new intersectional theory of oppression that’s ridiculous, fantastical, grossly racist, and allows the old bourgeoisie to play leading roles.”
35% : Torres “is fighting for his Jewish constituents in the Bronx,” yet Blake pretends that “his support for Jewish civil rights is solely about Israel.”
31% : “It’s less than surprising that” Latino citizens “would sour on the Trump administration and the Republican Party” if they now “feel like they’re being unfairly targeted” by ICE and aren’t feeling economic relief, warns National Review’s Jim Geragthy.

*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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