U.S. Reaches Agreement to Release Huawei Executive in Case That Strained Ties With China
- Bias Rating
-98% Very Liberal
- Reliability
N/AN/A
- Policy Leaning
90% Very Conservative
- Politician Portrayal
-43% Negative
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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
N/A
- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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-100%
Liberal
100%
Conservative
Contributing sentiments towards policy:
45% : The transaction appeared intended to avoid U.S.-led sanctions on Tehran.41% : While the charges focused on bank and wire fraud, in announcing the indictment, the Justice Department alleged that Huawei employees, including Ms. Meng, lied to bank officials when asked about whether Huawei was unlawfully engaged in business with Iran, knowing that U.S. sanctions on Tehran would prevent the banks from financing the sale.
39% : Ms. Meng spent the past nearly three years out on bail of about $8 million at her two luxurious homes in Vancouver, detained by Canadian authorities as the United States sought her extradition in a fraud case related to Huawei's sale of telecommunications equipment to Iran.
38% : Her determination to wire up Tehran, at a time in which the West was seeking to contain Iran's nuclear program, attracted protests among American officials.
37% : But she refused to plead guilty to bank and wire fraud charges stemming from Huawei's deal in Iran.
28% : "It sends the wrong message to Chinese business executives around the world that it's permissible to engage in fraudulent transactions with Iran and North Korea," said Michael Pillsbury, a scholar at the Hudson Institute who was a top China adviser to former President Donald J. Trump.
*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.