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Gulf Digital News Article Rating

Heavy snow expected in parts of US

  • Bias Rating
  • Reliability

    25% ReliableLimited

  • Policy Leaning

    -10% Center

  • Politician Portrayal

    -63% 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

-31% Negative

  •   Liberal
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Bias Meter

Contributing sentiments towards policy:

48% : "With the extreme cold in the North and the storm, half of all Americans are under some form of weather advisories," said Brian Hurley, a meteorologist with the NWS's Weather Prediction Centre in College Park, Maryland. Agricultural meteorologists said the heavy snow and ice should benefit dormant winter wheat crops in Oklahoma, where 23 per cent of the state is in severe drought, according to a weekly US Drought Monitor report.
48% : Livestock will face stressful conditions due to ice and snow in the Southern Plains and extreme cold in the north, the USDA said. New York City, Boston, Baltimore and Washington, DC, could receive 4 to 10 inches of heavy, wet snow starting tomorrow, Hurley said, with temperatures in the low -5.5C in DC, with Boston seeing a low of -14C. Throughout the storm, New York state was expected to be under a "Code Blue," which requires social service providers to extend shelter hours and ensure the homeless have access to them.
47% : The storm, which could impact nearly half the country's population, will bring up to 20 inches of snow in the Appalachians and West Virginia mountains, while most people living in the eastern US could face dangerous slick or frozen roads and potential power outages from ice-laden trees and branches falling and snapping power lines, officials said.

*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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