Oil On Track For Weekly Gain On China Optimism

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Published Dec 15, 2023
Source Analysis Score
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The Source Analysis Score focuses on assessing the quality of sources and quotes used including their number, lengths, uniqueness, and diversity.
5% ReliablePoor
Bias Rating
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The Bias Rating is computed based on a number of factors including bias loaded words, sentiments towards certain political policies, author bias towards politicians, and the amount of tone found in the article.

-22% Somewhat Liberal

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*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.

Policy Leaning
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The policy leaning score is derived from author biases for or against a certain political policy, as found in articles.

-22% Somewhat Liberal

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-100%
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*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.

Politician Portrayal
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The politician leaning score is determined by the author's tone and leaning towards the specific politician mentioned in the article.

N/A

Overall Sentiment

28% Positive

Opposite Viewpoint
Category

Reliability Score Analysis

The Reliability Score of the article is determined on a percentage score basis from 0 to 100%.

  • Opposite Sources as Poor for the lower number of sources with different viewpoints.
  • Unique Sources as Poor for the lower number of different sources.
  • Multiple Sources as Poor for the lower number of total sources.
  • Multiple Quotes as Poor for the lower number of quotes used in the article.
  • Quote Length as Poor for the lower number of words used in each quote.

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.


Policy Leaning Analysis

This article includes the following sentiments, providing an average bias score of -22% Liberal:

  • 2 positive sentiments for Environmental Regulations


Policies:

Environmental Regulations

Sentiments

  •   Liberal
12% "The dollar wallowed near four-month lows after the U.S. Federal Reserve on Wednesday hinted at interest rate cuts next year -- a sign of ..."
10% "Oil prices rose slightly on Friday and remained on track for their first weekly gain in two months, thanks to a weaker dollar and ..."

*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. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.

Extremely
Liberal

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Moderately
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Somewhat Liberal

Center

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Moderately
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Very
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Contributing sentiments towards policy:

56% : The dollar wallowed near four-month lows after the U.S. Federal Reserve on Wednesday hinted at interest rate cuts next year -- a sign of hope for economic growth and oil demand.
55% : Oil prices rose slightly on Friday and remained on track for their first weekly gain in two months, thanks to a weaker dollar and a bullish forecast from the International Energy Agency (IEA) on oil demand.

*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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