Trump Is Clearly Rattled by What Mamdani Just Did in New York 83%

By Rachel Kahn0%

6/26/2026, 8:05:27 PM

BS Summary: This article contains 27 faulty reasoning types, including Biased Writer Voice, Confirmation Bias, and Appeal to Emotion, with Negativity Bias as the most egregious example at 50.2% saturation with 214 hits. Analysis detected 1,687 faulty-reasoning hits from 426 analyzed words, generating a BS Score of 74.6% and a BS Rank of 83% (3,699 of 21,176 articles). This article is worse (more manipulative) than 82.50% of the article peer group.

President Donald Trump spoke at the Faith & Freedom Coalition policy conference in Washington, D.C. on Friday, but seemed hyperfixated on something that has nothing to do with neither faith nor freedom: New York City’s rent freeze. 
“Mayor Mamdani—who came to the White House and seems like a nice guy—he said he was going to do this in his campaign. 
Nobody thought he was serious,” Trump said. 
On Thursday, New York City’s Rent Guidelines Board passed a rent freeze, enabling Mayor Zohran Mamdani to make good on one of his key campaign promises. 
The freeze will go into effect in October, and will impact tenants living in the city’s nearly one million rent-stabilized apartments. 
“First time ever, with a ruling, zero rent increases for landlords  despite the fact that energy, supplies, real estate taxes, and just about everything else has gone up,” Trump said. 
“They’re basically confiscating their property.” 
Contrary to what Trump said, rent freezes in NYC have been enacted in the past, most recently for three years under Mayor Bill de Blasio. 
But he’s right that prices are rising, partially due to his bungled tariffs and the war in Iran. 
“What the mayor doesn’t say is that these buildings will soon turn into ghettos and slums, and that everybody will continue leaving New York. 
And as this spreads throughout the country very much like an uncontrollable form of cancer, the country itself will be taken down,” the president said. 
Later in the speech, Trump went on to attack Mamdani’s DSA allies who won the Democratic primary in New York this week. 
“They will close your churches in this country, big old communists, and they’re trying to. 
They will kill your people…. 
This is the greatest threat to our country since its founding, in my opinion, 250 years ago, what’s happening right now. 
It’s the greatest threat.” 
“They’re animals, they’re animals. 
In many cases, they’re not smart, but in some cases they are.” 
It’s obvious that Trump is nervous, but maybe Mamdani’s rent freeze is just hitting a little too close to home for the NYC slumlord. 
In the 90s, Trump worked with his father to scam tenants in rent-regulated buildings, raising their rents while funneling money to each other, as uncovered by the New York Times in 2018. 
And in the 1980s, he made life a living hell for his rent-regulated tenants, trying to force them out of their homes so that he could tear down the building and make condos. 
Article reasoning-pattern comparisonThis article: 26.8%Rachel Kahn: 8.5%newrepublic.com: 6.1%Confirmation Bias26.8%This article: 0.0%Rachel Kahn: 1.0%newrepublic.com: 0.5%Anchoring Bias0.0%This article: 20.7%Rachel Kahn: 10.4%newrepublic.com: 3.3%Availability Heuristic20.7%This article: 0.0%Rachel Kahn: 0.7%newrepublic.com: 1.0%Representativeness Heuristic0.0%This article: 0.0%Rachel Kahn: 1.0%newrepublic.com: 0.8%Hindsight Bias0.0%This article: 13.1%Rachel Kahn: 5.1%newrepublic.com: 1.9%Overconfidence Bias13.1%This article: 17.1%Rachel Kahn: 16.1%newrepublic.com: 8.0%Framing Effect17.1%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.4%Loss Aversion0.0%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.3%Status Quo Bias0.0%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.1%Sunk Cost Effect0.0%This article: 6.1%Rachel Kahn: 0.9%newrepublic.com: 1.0%Optimism Bias6.1%This article: 15.5%Rachel Kahn: 5.3%newrepublic.com: 2.5%Pessimism Bias15.5%This article: 50.2%Rachel Kahn: 25.1%newrepublic.com: 13.0%Negativity Bias50.2%This article: 2.8%Rachel Kahn: 1.1%newrepublic.com: 0.9%Self-Serving Bias2.8%This article: 9.9%Rachel Kahn: 1.5%newrepublic.com: 1.8%Fundamental Attribution Error9.9%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.2%Actor-Observer Bias0.0%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 1.7%In-Group Bias0.0%This article: 0.0%Rachel Kahn: 2.4%newrepublic.com: 1.0%Out-Group Homogeneity Bias0.0%This article: 5.4%Rachel Kahn: 1.7%newrepublic.com: 1.3%Halo Effect5.4%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.6%Horn Effect0.0%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.0%Dunning-Kruger Effect0.0%This article: 5.9%Rachel Kahn: 2.2%newrepublic.com: 1.4%Recency Bias5.9%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.5%Primacy Effect0.0%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.1%Blind-Spot Bias0.0%This article: 18.1%Rachel Kahn: 8.2%newrepublic.com: 3.7%Ad Hominem18.1%This article: 0.0%Rachel Kahn: 1.9%newrepublic.com: 1.1%Straw Man0.0%This article: 13.4%Rachel Kahn: 2.8%newrepublic.com: 3.4%Appeal to Authority13.4%This article: 10.6%Rachel Kahn: 3.3%newrepublic.com: 1.9%False Dilemma10.6%This article: 11.5%Rachel Kahn: 8.6%newrepublic.com: 1.9%Slippery Slope11.5%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.3%Circular Reasoning0.0%This article: 10.8%Rachel Kahn: 9.6%newrepublic.com: 7.9%Hasty Generalization10.8%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.3%Red Herring0.0%This article: 3.5%Rachel Kahn: 0.5%newrepublic.com: 0.7%Bandwagon3.5%This article: 26.3%Rachel Kahn: 24.1%newrepublic.com: 6.3%Appeal to Emotion26.3%This article: 8.5%Rachel Kahn: 1.3%newrepublic.com: 1.8%Begging the Question8.5%This article: 10.3%Rachel Kahn: 4.3%newrepublic.com: 3.2%Post Hoc (False Cause)10.3%This article: 15.3%Rachel Kahn: 2.4%newrepublic.com: 0.3%Tu Quoque15.3%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.9%Burden of Proof0.0%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.1%Appeal to Nature0.0%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.3%Composition/Division0.0%This article: 0.0%Rachel Kahn: 6.5%newrepublic.com: 2.0%Anecdotal0.0%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.2%No True Scotsman0.0%This article: 21.1%Rachel Kahn: 3.3%newrepublic.com: 1.8%Ambiguity (Equivocation)21.1%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.1%Middle Ground0.0%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.2%Personal Incredulity0.0%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.2%Special Pleading0.0%This article: 7.5%Rachel Kahn: 3.5%newrepublic.com: 0.3%Genetic Fallacy7.5%This article: 5.4%Rachel Kahn: 9.1%newrepublic.com: 2.3%Unattributed Quote5.4%This article: 2.8%Rachel Kahn: 3.2%newrepublic.com: 1.6%Quote-first Misdirection2.8%This article: 32.4%Rachel Kahn: 37.7%newrepublic.com: 15.2%Biased Writer Voice32.4%This article: 0.0%Rachel Kahn: 2.2%newrepublic.com: 2.4%Indoctrination0.0%This article: 25.1%Rachel Kahn: 21.2%newrepublic.com: 7.2%Politically Left Leaning Bias25.1%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.6%Politically Right Leaning Bias0.0%This article: 0.0%Rachel Kahn: 0.0%newrepublic.com: 0.3%Attempt to Sell a Product or S…0.0%

426 words analyzed.

Speakers

3speakers55%attributed speech192writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 100.0% coverageWriter's voice • 37 words • 100.0% coverageTrump • 23 words • 100.0% coverageTrump • 7 words • 0.0% coverageRent Guidelines Board • 26 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageTrump • 31 words • 0.0% coverageTrump • 5 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 18 words • 100.0% coverageTrump • 24 words • 0.0% coverageTrump • 25 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageTrump • 15 words • 0.0% coverageTrump • 5 words • 0.0% coverageTrump • 21 words • 0.0% coverageTrump • 4 words • 0.0% coverageTrump • 4 words • 0.0% coverageTrump • 12 words • 0.0% coverageWriter's voice • 24 words • 100.0% coverageNew York Times • 32 words • 100.0% coverageWriter's voice • 33 words • 100.0% coverage
Selected voice

New York Times

100%flagged-word coverage
32 attributed words14% of attributed speech89% writer coverage
0%50.0%100.0%Politically Left Leaning B+60.9 ptsWriter: 39.1%New York Times: 100.0%100.0%Biased Writer Voice+44.8 ptsWriter: 55.2%New York Times: 100.0%100.0%Quote-first Misdirection-6.3 ptsWriter: 6.3%New York Times: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.