The Graham Platner Receipts on Dems Were Whipped Out...by a CNN Host? ⁠89%

By Matt Vespa⁠78%

7/8/2026, 7:00:04 AM

BS Summary: This article contains 34 faulty reasoning types, including Negativity Bias, Biased Writer Voice, and Unattributed Quote, with Appeal to Emotion as the most egregious example at 51.5% saturation with 152 hits. Analysis detected 1,873 faulty-reasoning hits from 295 analyzed words, generating a BS Score of 82.1% and a BS Rank of ⁠89% (2,342 of 20,472 articles). This article is worse (more manipulative) than 88.60% of the article peer group.

I never thought Abby Philip, of all people, would present the receipts on CNN, but she did. 
She’s known for interrupting conservative guests as they’re about to tear apart a weak liberal talking point or falsely deny that a prominent Democrat ever said something foolish. 
We saw that when Scott Jennings claimed Tim Walz compared the ICE raids in Minneapolis to Gettysburg. 
Abby, he did say that—and I’m sure that speech was broadcast on your network. 
Unfortunately, with Graham Platner facing rape allegations that threaten Democratic prospects in Maine, the CNN host isn’t letting Democrats, who fully supported Platner despite the Nazi tattoo and other baggage, off the hook: 
“In the wake of new rape allegations that he categorically denies, Graham Platner still hasn't made an official decision, but he has lost support from virtually every prominent Democrat who initially backed him. 
Senators Bernie Sanders, Elizabeth Warren, Chuck Schumer, Kirsten Gillibrand, Ro Khanna, they are all now calling for Platner to withdraw from the selection after sticking with him through previous sexual misconduct allegations, and reports that he had a Nazi Tattoo on his chest.” 
…The New York Times reports that in a private call with campaign staff, Platner said that he believes he still has leverage to influence the decision on his replacement.” 
I mean, guys, everyone saw this coming. 
Either you have ostrich syndrome, or you’re that clueless. 
Either way, we’re all enjoying the circus you created. 
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Article reasoning-pattern comparisonThis article: 10.2%Matt Vespa: 5.9%Townhall: 5.2%Confirmation Bias10.2%This article: 0.0%Matt Vespa: 0.7%Townhall: 0.7%Anchoring Bias0.0%This article: 19.7%Matt Vespa: 2.7%Townhall: 2.8%Availability Heuristic19.7%This article: 0.0%Matt Vespa: 0.9%Townhall: 0.8%Representativeness Heuristic0.0%This article: 2.4%Matt Vespa: 1.2%Townhall: 0.7%Hindsight Bias2.4%This article: 0.0%Matt Vespa: 0.9%Townhall: 1.7%Overconfidence Bias0.0%This article: 30.5%Matt Vespa: 8.8%Townhall: 11.4%Framing Effect30.5%This article: 11.2%Matt Vespa: 0.5%Townhall: 0.3%Loss Aversion11.2%This article: 0.0%Matt Vespa: 0.2%Townhall: 0.3%Status Quo Bias0.0%This article: 0.0%Matt Vespa: 0.1%Townhall: 0.1%Sunk Cost Effect0.0%This article: 4.7%Matt Vespa: 1.2%Townhall: 1.5%Optimism Bias4.7%This article: 11.2%Matt Vespa: 2.3%Townhall: 1.9%Pessimism Bias11.2%This article: 49.5%Matt Vespa: 13.9%Townhall: 13.5%Negativity Bias49.5%This article: 3.1%Matt Vespa: 1.2%Townhall: 1.8%Self-Serving Bias3.1%This article: 0.0%Matt Vespa: 1.5%Townhall: 1.8%Fundamental Attribution Error0.0%This article: 0.0%Matt Vespa: 0.1%Townhall: 0.1%Actor-Observer Bias0.0%This article: 29.8%Matt Vespa: 5.3%Townhall: 4.7%In-Group Bias29.8%This article: 9.5%Matt Vespa: 2.8%Townhall: 3.2%Out-Group Homogeneity Bias9.5%This article: 9.5%Matt Vespa: 2.1%Townhall: 1.9%Halo Effect9.5%This article: 0.0%Matt Vespa: 1.8%Townhall: 0.8%Horn Effect0.0%This article: 0.0%Matt Vespa: 0.0%Townhall: 0.0%Dunning-Kruger Effect0.0%This article: 11.2%Matt Vespa: 1.2%Townhall: 1.3%Recency Bias11.2%This article: 12.2%Matt Vespa: 0.8%Townhall: 0.6%Primacy Effect12.2%This article: 0.0%Matt Vespa: 0.1%Townhall: 0.0%Blind-Spot Bias0.0%This article: 6.1%Matt Vespa: 6.5%Townhall: 5.1%Ad Hominem6.1%This article: 9.5%Matt Vespa: 1.3%Townhall: 2.0%Straw Man9.5%This article: 29.2%Matt Vespa: 4.0%Townhall: 4.4%Appeal to Authority29.2%This article: 6.1%Matt Vespa: 2.3%Townhall: 2.0%False Dilemma6.1%This article: 0.0%Matt Vespa: 2.5%Townhall: 1.6%Slippery Slope0.0%This article: 0.0%Matt Vespa: 0.3%Townhall: 0.1%Circular Reasoning0.0%This article: 28.1%Matt Vespa: 9.7%Townhall: 9.2%Hasty Generalization28.1%This article: 5.8%Matt Vespa: 0.4%Townhall: 0.5%Red Herring5.8%This article: 16.9%Matt Vespa: 1.6%Townhall: 1.3%Bandwagon16.9%This article: 51.5%Matt Vespa: 9.4%Townhall: 11.3%Appeal to Emotion51.5%This article: 9.2%Matt Vespa: 2.5%Townhall: 2.3%Begging the Question9.2%This article: 0.0%Matt Vespa: 2.0%Townhall: 2.5%Post Hoc (False Cause)0.0%This article: 0.0%Matt Vespa: 0.3%Townhall: 0.6%Tu Quoque0.0%This article: 11.2%Matt Vespa: 2.1%Townhall: 1.5%Burden of Proof11.2%This article: 0.0%Matt Vespa: 0.1%Townhall: 0.1%Appeal to Nature0.0%This article: 0.0%Matt Vespa: 0.2%Townhall: 0.1%Composition/Division0.0%This article: 15.6%Matt Vespa: 2.3%Townhall: 1.4%Anecdotal15.6%This article: 0.0%Matt Vespa: 0.3%Townhall: 0.2%No True Scotsman0.0%This article: 18.3%Matt Vespa: 1.9%Townhall: 2.2%Ambiguity (Equivocation)18.3%This article: 0.0%Matt Vespa: 0.0%Townhall: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Matt Vespa: 0.0%Townhall: 0.0%Middle Ground0.0%This article: 5.8%Matt Vespa: 0.2%Townhall: 0.2%Personal Incredulity5.8%This article: 0.0%Matt Vespa: 0.0%Townhall: 0.2%Special Pleading0.0%This article: 0.0%Matt Vespa: 0.3%Townhall: 0.4%Genetic Fallacy0.0%This article: 40.3%Matt Vespa: 3.2%Townhall: 3.3%Unattributed Quote40.3%This article: 25.8%Matt Vespa: 2.9%Townhall: 3.0%Quote-first Misdirection25.8%This article: 49.5%Matt Vespa: 19.1%Townhall: 16.3%Biased Writer Voice49.5%This article: 39.0%Matt Vespa: 4.7%Townhall: 5.7%Indoctrination39.0%This article: 11.2%Matt Vespa: 0.7%Townhall: 0.2%Politically Left Leaning Bias11.2%This article: 26.4%Matt Vespa: 13.4%Townhall: 14.0%Politically Right Leaning Bias26.4%This article: 14.9%Matt Vespa: 5.5%Townhall: 5.1%Attempt to Sell a Product or S…14.9%

295 words analyzed.

Speakers

2speakers20%attributed speech235writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 100.0% coverageWriter's voice • 17 words • 100.0% coverageWriter's voice • 28 words • 100.0% coverageWriter's voice • 17 words • 100.0% coverageWriter's voice • 14 words • 100.0% coverageWriter's voice • 33 words • 100.0% coverageWriter's voice • 33 words • 100.0% coverageWriter's voice • 43 words • 100.0% coverageThe New York Times • 29 words • 100.0% coverageWriter's voice • 7 words • 100.0% coverageWriter's voice • 9 words • 100.0% coverageWriter's voice • 9 words • 100.0% coverageTownhall • 17 words • 100.0% coverageWriter's voice • 13 words • 100.0% coverageTownhall • 14 words • 100.0% coverage
Selected voice

Townhall

100%flagged-word coverage
31 attributed words52% of attributed speech100% writer coverage
0%50.0%100.0%Attempt to Sell a Product +94.5 ptsWriter: 5.5%Townhall: 100.0%100.0%Biased Writer Voice-62.1 ptsWriter: 62.1%Townhall: 0.0%0.0%Politically Right Leaning +28.9 ptsWriter: 26.0%Townhall: 54.8%54.8%Indoctrination+13.1 ptsWriter: 41.7%Townhall: 54.8%54.8%Unattributed Quote-38.3 ptsWriter: 38.3%Townhall: 0.0%0.0%Quote-first Misdirection-32.3 ptsWriter: 32.3%Townhall: 0.0%0.0%Politically Left Leaning B-14.0 ptsWriter: 14.0%Townhall: 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.