Democrats Could Learn Something From the Rise of the Whigs
- Bias Rating
10% Center
- Reliability
65% ReliableFair
- Policy Leaning
10% Center
- Politician Portrayal
-39% 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
44% Positive
- Liberal
- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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Contributing sentiments towards policy:
61% : But Trump likes to compare himself to Jackson, a fellow celebrity who led a revolt against the establishment of the time, and the comparison is more compelling now than it was when Trump won in 2016.59% : This is due not only to the fact that Trump won the popular vote this time, but also to how he got there.
48% : But there are warning signs from the election, in which once-solid parts of the Democratic coalition shifted toward Trump.
47% : To compete in the South and Midwest, as well as in Pennsylvania and New York, they had to make room in their party for states' rights proponents and Anti-Masonic populists without alienating too much of their existing base of northeastern merchants and professionals.
45% : These factions generally supported infrastructure projects, pro-banking policies and government intervention to support economic recovery in downturns.
28% : Two of his salient policies were similar to Trump's: a purge of the civil service ("to the victor belongs the spoils") and mass deportations (of the Five Tribes).
20% : Such a pitch may have broad appeal if Trump spends his first two years back in office indulging his worst impulses.
13% : Like Trump in 2020, Jackson reacted poorly to defeat.
13% : The good news is that the victory margins for Trump and Congressional Republicans were relatively small, and Trump is ineligible to run again.
*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.