Raw Story⁠93%

Money will probably matter most for Trump's presidential pick: analyst ⁠85%

By María Teresita Armstrong-Matta⁠90%

7/20/2026, 6:00:01 PM

BS Summary: This article contains 21 faulty reasoning types, including Confirmation Bias, Burden of Proof, and Overconfidence Bias, with Biased Writer Voice as the most egregious example at 44.5% saturation with 77 hits. Analysis detected 539 faulty-reasoning hits from 173 analyzed words, generating a BS Score of 76.5% and a BS Rank of ⁠85% (3,401 of 21,887 articles). This article is worse (more manipulative) than 84.50% of the article peer group.

President Donald Trump has signaled his preference for Don Jr. as the 2028 presidential successor over Vice President JD Vance and Secretary of State Marco Rubio. 
According to analyst Jonathan V. 
Last of The Bulwark, Trump Media & Technology Group's new Truth Social API product represents infrastructure building for family financial gain. 
It also gives subscribers early access to posts before public release. 
"But believe me: This story is fascinating," Last wrote. 
"It demonstrates Trump's animal cunning. 
And it points to yet another vulnerability in America's economic and social order. 
One that we hadn't even realized existed." 
Last argues Trump is systematically building wealth-generating infrastructure for his family's control of the Republican Party, and says, "Truth API is worth probably a few hundred million dollars a year if a Trump is president, or is presumed to have a 50-50 chance to be president." 
But, "It is worth zero dollars if Marco Rubio or JD Vance is president," he added. 
Watch the video below. 
Article reasoning-pattern comparisonThis article: 35.8%María Teresita Armstrong-Matta: 9.8%Rawstory: 8.4%Confirmation Bias35.8%This article: 5.8%María Teresita Armstrong-Matta: 3.6%Rawstory: 0.8%Anchoring Bias5.8%This article: 0.0%María Teresita Armstrong-Matta: 4.4%Rawstory: 4.5%Availability Heuristic0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.9%Rawstory: 1.1%Representativeness Heuristic0.0%This article: 4.0%María Teresita Armstrong-Matta: 0.6%Rawstory: 1.0%Hindsight Bias4.0%This article: 32.4%María Teresita Armstrong-Matta: 5.8%Rawstory: 2.2%Overconfidence Bias32.4%This article: 0.0%María Teresita Armstrong-Matta: 15.6%Rawstory: 13.4%Framing Effect0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.4%Loss Aversion0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.3%Rawstory: 0.4%Status Quo Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.1%Sunk Cost Effect0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.6%Rawstory: 0.7%Optimism Bias0.0%This article: 7.5%María Teresita Armstrong-Matta: 2.3%Rawstory: 2.9%Pessimism Bias7.5%This article: 27.7%María Teresita Armstrong-Matta: 20.7%Rawstory: 21.6%Negativity Bias27.7%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 1.2%Self-Serving Bias0.0%This article: 12.1%María Teresita Armstrong-Matta: 7.0%Rawstory: 2.8%Fundamental Attribution Error12.1%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.3%Actor-Observer Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 1.6%Rawstory: 2.5%In-Group Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.6%Rawstory: 1.6%Out-Group Homogeneity Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.6%Halo Effect0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.7%Rawstory: 0.9%Horn Effect0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.0%Dunning-Kruger Effect0.0%This article: 5.2%María Teresita Armstrong-Matta: 1.1%Rawstory: 1.8%Recency Bias5.2%This article: 0.0%María Teresita Armstrong-Matta: 0.4%Rawstory: 0.7%Primacy Effect0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.1%Blind-Spot Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 10.2%Rawstory: 6.3%Ad Hominem0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.6%Rawstory: 0.7%Straw Man0.0%This article: 8.7%María Teresita Armstrong-Matta: 3.3%Rawstory: 4.1%Appeal to Authority8.7%This article: 9.2%María Teresita Armstrong-Matta: 3.8%Rawstory: 3.0%False Dilemma9.2%This article: 7.5%María Teresita Armstrong-Matta: 0.3%Rawstory: 1.5%Slippery Slope7.5%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.2%Circular Reasoning0.0%This article: 26.6%María Teresita Armstrong-Matta: 7.7%Rawstory: 12.1%Hasty Generalization26.6%This article: 0.0%María Teresita Armstrong-Matta: 0.6%Rawstory: 0.7%Red Herring0.0%This article: 0.0%María Teresita Armstrong-Matta: 1.2%Rawstory: 0.8%Bandwagon0.0%This article: 2.9%María Teresita Armstrong-Matta: 6.7%Rawstory: 9.2%Appeal to Emotion2.9%This article: 0.0%María Teresita Armstrong-Matta: 2.8%Rawstory: 1.6%Begging the Question0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.8%Rawstory: 3.8%Post Hoc (False Cause)0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.6%Tu Quoque0.0%This article: 35.8%María Teresita Armstrong-Matta: 3.7%Rawstory: 1.7%Burden of Proof35.8%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.1%Appeal to Nature0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.6%Rawstory: 0.5%Composition/Division0.0%This article: 12.1%María Teresita Armstrong-Matta: 1.2%Rawstory: 3.9%Anecdotal12.1%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.3%No True Scotsman0.0%This article: 0.0%María Teresita Armstrong-Matta: 3.1%Rawstory: 2.4%Ambiguity (Equivocation)0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.0%Gambler’s Fallacy0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.1%Middle Ground0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.2%Personal Incredulity0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.1%Special Pleading0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.4%Genetic Fallacy0.0%This article: 2.9%María Teresita Armstrong-Matta: 4.2%Rawstory: 5.3%Unattributed Quote2.9%This article: 5.2%María Teresita Armstrong-Matta: 4.6%Rawstory: 4.1%Quote-first Misdirection5.2%This article: 44.5%María Teresita Armstrong-Matta: 9.1%Rawstory: 15.7%Biased Writer Voice44.5%This article: 6.9%María Teresita Armstrong-Matta: 3.3%Rawstory: 3.2%Indoctrination6.9%This article: 12.1%María Teresita Armstrong-Matta: 6.2%Rawstory: 8.0%Politically Left Leaning Bias12.1%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 1.0%Politically Right Leaning Bias0.0%This article: 6.4%María Teresita Armstrong-Matta: 0.5%Rawstory: 0.5%Attempt to Sell a Product or S…6.4%

173 words analyzed.

Speakers

1speaker68%attributed speech56writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 10 words • 100.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 5 words • 100.0% coverageLast • 21 words • 100.0% coverageWriter's voice • 11 words • 100.0% coverageLast • 9 words • 100.0% coverageLast • 5 words • 100.0% coverageLast • 13 words • 0.0% coverageLast • 7 words • 100.0% coverageLast • 46 words • 100.0% coverageLast • 16 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverage
Selected voice

Last

100%flagged-word coverage
117 attributed words100% of attributed speech46% writer coverage
0%30.0%60.0%Biased Writer Voice+39.4 ptsWriter: 17.9%Last: 57.3%57.3%Attempt to Sell a Product -19.6 ptsWriter: 19.6%Last: 0.0%0.0%Politically Left Leaning B+17.9 ptsWriter: 0.0%Last: 17.9%17.9%Indoctrination+10.3 ptsWriter: 0.0%Last: 10.3%10.3%Unattributed Quote-8.9 ptsWriter: 8.9%Last: 0.0%0.0%Quote-first Misdirection+7.7 ptsWriter: 0.0%Last: 7.7%7.7%

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.