BS Summary: This article contains 15 faulty reasoning types, including Framing Effect, Biased Writer Voice, and Appeal to Emotion, with Negativity Bias as the most egregious example at 41.6% saturation with 47 hits. Analysis detected 414 faulty-reasoning hits from 113 analyzed words, generating a BS Score of 60% and a BS Rank of 66% (7,307 of 21,203 articles). This article is worse (more manipulative) than 65.50% of the article peer group.

A crowd of thousands transformed a block of the National Mall into an evangelical-style worship service Sunday at an event backed by President Donald Trump and funded with millions of taxpayer dollars. 
The lineup of influential speakers and their backgrounds. 
How the event ties into broader debates on church-state separation. 
A crowd of thousands are gathering at the National Mall for a prayer festival featuring Trump administration officials that aims to link the United States' founding with Christianity. 
Critics argue the event distorts history and blurs the line separating of church and state. 
Protests are planned by groups opposed to religious nationalism. 
Article reasoning-pattern comparisonThis article: 13.3%Michelle Boorstein: 7.8%The Washington Post: 3.8%Confirmation Bias13.3%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 1.3%Anchoring Bias0.0%This article: 24.8%Michelle Boorstein: 1.6%The Washington Post: 4.9%Availability Heuristic24.8%This article: 0.0%Michelle Boorstein: 2.2%The Washington Post: 1.0%Representativeness Heuristic0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.5%Hindsight Bias0.0%This article: 0.0%Michelle Boorstein: 0.3%The Washington Post: 1.2%Overconfidence Bias0.0%This article: 37.2%Michelle Boorstein: 22.8%The Washington Post: 21.5%Framing Effect37.2%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.8%Loss Aversion0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.9%Status Quo Bias0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.1%Sunk Cost Effect0.0%This article: 0.0%Michelle Boorstein: 5.2%The Washington Post: 3.6%Optimism Bias0.0%This article: 0.0%Michelle Boorstein: 1.8%The Washington Post: 3.6%Pessimism Bias0.0%This article: 41.6%Michelle Boorstein: 14.9%The Washington Post: 18.5%Negativity Bias41.6%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 1.5%Self-Serving Bias0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.9%Fundamental Attribution Error0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.1%Actor-Observer Bias0.0%This article: 8.0%Michelle Boorstein: 5.5%The Washington Post: 2.2%In-Group Bias8.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.8%Out-Group Homogeneity Bias0.0%This article: 0.0%Michelle Boorstein: 2.8%The Washington Post: 2.1%Halo Effect0.0%This article: 0.0%Michelle Boorstein: 1.8%The Washington Post: 0.4%Horn Effect0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Michelle Boorstein: 0.4%The Washington Post: 2.4%Recency Bias0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 1.0%Primacy Effect0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.0%Blind-Spot Bias0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.9%Ad Hominem0.0%This article: 0.0%Michelle Boorstein: 1.2%The Washington Post: 0.1%Straw Man0.0%This article: 28.3%Michelle Boorstein: 8.1%The Washington Post: 5.2%Appeal to Authority28.3%This article: 0.0%Michelle Boorstein: 0.4%The Washington Post: 1.5%False Dilemma0.0%This article: 0.0%Michelle Boorstein: 5.2%The Washington Post: 1.0%Slippery Slope0.0%This article: 0.0%Michelle Boorstein: 0.9%The Washington Post: 0.1%Circular Reasoning0.0%This article: 24.8%Michelle Boorstein: 7.6%The Washington Post: 5.9%Hasty Generalization24.8%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.1%Red Herring0.0%This article: 28.3%Michelle Boorstein: 0.8%The Washington Post: 0.5%Bandwagon28.3%This article: 34.5%Michelle Boorstein: 12.6%The Washington Post: 6.3%Appeal to Emotion34.5%This article: 0.0%Michelle Boorstein: 4.7%The Washington Post: 1.0%Begging the Question0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 4.5%Post Hoc (False Cause)0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.2%Tu Quoque0.0%This article: 0.0%Michelle Boorstein: 0.6%The Washington Post: 0.6%Burden of Proof0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.1%Appeal to Nature0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.1%Composition/Division0.0%This article: 0.0%Michelle Boorstein: 0.6%The Washington Post: 1.9%Anecdotal0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.2%No True Scotsman0.0%This article: 13.3%Michelle Boorstein: 0.8%The Washington Post: 2.7%Ambiguity (Equivocation)13.3%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.1%Middle Ground0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.0%Personal Incredulity0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.1%Special Pleading0.0%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 0.2%Genetic Fallacy0.0%This article: 0.0%Michelle Boorstein: 3.3%The Washington Post: 4.8%Unattributed Quote0.0%This article: 9.7%Michelle Boorstein: 5.2%The Washington Post: 2.5%Quote-first Misdirection9.7%This article: 36.3%Michelle Boorstein: 10.4%The Washington Post: 15.2%Biased Writer Voice36.3%This article: 24.8%Michelle Boorstein: 6.6%The Washington Post: 2.0%Indoctrination24.8%This article: 13.3%Michelle Boorstein: 7.6%The Washington Post: 3.6%Politically Left Leaning Bias13.3%This article: 28.3%Michelle Boorstein: 8.2%The Washington Post: 1.4%Politically Right Leaning Bias28.3%This article: 0.0%Michelle Boorstein: 0.0%The Washington Post: 1.5%Attempt to Sell a Product or S…0.0%

113 words analyzed.

Speakers

No attributed speakers were identified in this analysis.

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Analysis

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