Investments in Solar Power Eclipse Oil for First Time
- Bias Rating
-10% Center
- Reliability
55% ReliableFair
- Policy Leaning
-10% Center
- Politician Portrayal
16% Negative
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By creating an account, you agree to our Terms and Privacy Policy, and subscribe to email updates. Already a member: Log inBias 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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- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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Contributing sentiments towards policy:
60% : The figure marks a sharp increase from previous years and highlights the growing divergence between clean-energy spending and traditional fossil-fuel industries such as oil, gas and coal.59% : While investments in clean energy have been strong, they haven't been evenly split.
58% : Spending on so-called clean-energy projects -- which includes renewable energy, electric vehicles, low-carbon hydrogen and battery storage, among other things -- is rising at a "striking" rate and vastly outpacing spending on traditional fossil fuels, Fatih Birol, the IEA's executive director said in an interview.
57% : Investments in clean energy and fossil fuels were largely neck-and-neck in the years leading up to the pandemic, but have diverged sharply since.
50% : They are often financially unable to dole out large sums on subsidies and state backing, as the U.S., European Union and China have done.
50% : The powerful economic rebound that followed the end of lockdown measures across most of the globe helped prompt the divergence between spending on clean energy and fossil fuels.
44% : This includes mushrooming government spending aimed at driving adherence to global climate targets such as President Biden's Inflation Reduction Act.
*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.