Keyword summary
⁠24%1 analyzed article/video1,442 analyzed words
BS Summary: These Neural Networks results contain 24 faulty reasoning types, including Framing Effect, Ambiguity (Equivocation), and Optimism Bias, with Negativity Bias as the most egregious example at 8.1% saturation with 466 hits. Analysis detected 2,505 faulty-reasoning hits from 5,768 analyzed words across 1 article, generating a BS Score of 1.8% and a BS Rank of ⁠18% (22,972 of 27,874 keywords). This Neural Networks is better (less manipulative) than 82.40% of the peer group.
Neural Networks
Keyword ranking list
PercentileKeywordBS Score
⁠0%Self-Driving Cars1%
⁠0%Self Driving Cars1%
⁠0%Bastille Day1%
⁠0%Anthony Broadwater1%
⁠0%Alice Sebold1%
⁠18%Neural Networks (selected)2%
⁠100%Rad Power Bikes60%
⁠100%Mike Lewis60%
⁠100%Joni Balter60%
⁠100%Lawrence O'donnell69%
⁠100%Bondi Beach Shooting70%
Keyword details
Total words: 5,768
Article count: 1
Authors
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Attribute Prevalence (Top 48)
Neural Networks attribute prevalence percentages (biases/fallacies), sorted highest to lowest.
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Neural Networks vs sitewide
Neural Networks attribute percentages, with an overlaid sitewide baseline for those same attributes.

Analyzed articles and videos