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The Epoch Times Article Rating

Handling of Mar-a-Lago Raid Breeding Damaging Distrust in Law Enforcement: Expert

  • Bias Rating
  • Reliability

    N/AN/A

  • Policy Leaning

    -10% Center

  • Politician Portrayal

    -4% 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:

56% : American law enforcement runs on trust, Letts said.
56% : Law enforcement agencies have to cooperate to do their work, Letts said.
47% : It also impacts the inner workings of law enforcement.
45% : Without explanations, acts like the Mar-a-Lago raid create distrust between local and federal law enforcement, he said.
43% : They also create civilian distrust for law enforcement in general.
43% : The FBI made several decisions at Mar-a-Lago that could catastrophically damage trust in law enforcement, Letts said.
43% : The FBI's Mar-a-Lago raid will also cause the public to distrust state and local police, Letts said, as most of the time, the public doesn't see the difference between local police, state police, and federal law enforcement.
41% : Even law enforcement on drug dealing will fall apart if the FBI and police don't trust each other, he said.
39% : Since then, reports have been spreading about an internal FBI and DHS bulletin, leaked in part by CNN, NBC, and CBS, of an increase in bomb threats made online to law enforcement and officials following the Mar-a-Lago raid.
35% : Unless trust is restored, the FBI's Mar-a-Lago raid may begin the "collapse" of American law enforcement, police expert Michael Letts said.
30% : Without someone else present, law enforcement could potentially plant fake evidence or steal a suspect's property, Letts 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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