National Review Article RatingHow Not to Be Caught Saying Hideous Things: A Primer | National Review
- Bias Rating
- Reliability
60% ReliableAverage
- Policy Leaning
66% Medium Right
- Politician Portrayal
N/A
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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
2% Positive
- Conservative
| Sentence | Sentiment | Bias |
|---|---|---|
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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-100%
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Contributing sentiments towards policy:
45% : In some circumstances, it involves me not placing my hands on a keyboard and typing those sentiments out; in others, it involves not saying them aloud.41% : If Jones had used my technique -- that is, if he had simply not fantasized about pissing on his colleagues' graves, murdering politicians, or killing children to advance his political aims -- he'd never have got himself into this mess in the first place.
38% : I have developed a strategy to avoid being caught saying that I hate all cops, am a communist, or believe that all white, rural Americans are racist idiots, and, in my infinite benevolence, I would like to share it with Platner -- and others -- for free.
37% : They talked about raping their enemies and driving them to suicide and lauded Republicans who they believed support slavery.
*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.