Lithium Start-Up Seeks Cash From Berlin to Bring Project to Life

  • Bias Rating

    -6% Center

  • Reliability

    40% ReliableFair

  • Policy Leaning

    -16% Somewhat Liberal

  • Politician Portrayal

    N/A

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

N/A

  •   Liberal
SentenceSentimentBias
"The European Union and the US are seeking to challenge China's dominance in a global competition to produce materials that have applications in everything from health care to electric vehicles."
Positive
16% Conservative
"We are convinced that our pitch comes at the right time as the European Union is pushing to reduce its dependence on China as one of the main suppliers for battery materials, Wedin said."
Positive
0% Conservative
"then-senator Carl Levin asked another former Goldman executive, Daniel Sparks, in 2010."
Negative
-2% Liberal
"then-senator Carl Levin asked another former Goldman executive, Daniel Sparks, in 2010."
Negative
-2% Liberal
"Sparks said Montag was referring to Goldman's performance on Timberwolf, not the deal itself."
Negative
-20% Liberal

Extremely
Liberal

Very
Liberal

Moderately
Liberal

Somewhat Liberal

Center

Somewhat Conservative

Moderately
Conservative

Very
Conservative

Extremely
Conservative

-100%
Liberal

100%
Conservative

Contributing sentiments towards policy:

58% :The European Union and the US are seeking to challenge China's dominance in a global competition to produce materials that have applications in everything from health care to electric vehicles.
50% : "We are convinced that our pitch comes at the right time as the European Union is pushing to reduce its dependence on China as one of the main suppliers for battery materials," Wedin 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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