Trump Person of the Year Interview and Cabinet Pick News: Transition Live Updates
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- Policy Leaning
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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
4% Positive
- Liberal
- Conservative
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Policy Leaning Analysis
Politician Portrayal Analysis
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Contributing sentiments towards policy:
60% : The share of people gaining access to electricity has steadily grown globally, and fossil fuels are largely responsible.58% : And it was made from fossil fuels," read the signs.
57% : In some places, renewable energy has been able to displace fossil fuels.
54% : "The argument offered by Mr. Wright, who has been chosen by President-elect Donald J. Trump to run the Energy Department, ignores the fact that wind, solar and other renewable energy are cleaner and increasingly cheaper than fossil fuels.
54% : "But by sheathing fossil fuels in humanitarian language as a solution to global poverty, Mr. Wright has emerged as one of the right's most savvy salesmen for oil and gas.
54% : Fossil fuels remain critical to powering factories and industries needed to spur real economic prosperity, he said.
52% : "If a lot more executives in the oil and gas industry would make this argument, and make this intellectual case for the use of fossil fuels, I think the energy industry as a whole would have a lot better PR success," Mr. Peeples said.
50% : But Ian Muir, head of insights at Catalyst Energy Advisors, a consulting firm, pointed out that renewables were now cheaper than fossil fuels in most countries where people lack electricity.
48% : "It's perhaps based in the need to sell fossil fuels and shroud it in a moral framework.
46% : It recommended nations make an immediate and drastic shift away from fossil fuels to prevent the planet from crossing a critical threshold for global warming within the next decade.
*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.