Fact checking News

Fact checking News

Urban Legends

Falsehood flies and the truth comes limping after

Filter numbers online


What is fake news? Is Donald Trump correct when he says CNN, The New York Times, and other mainstream outlets report fake news?
Commentator and bestselling author Andrew Klavan explains...


How do you rate: CNN?

source:
https://MediaBiasFactCheck.com



Source of truth? :D


Že vysíláme fake news? Ať si udělá každý názor, my pracujeme s fakty, říká pracovník ruské televize
Ivor Crotty
RT
RTV


CNN fake news from London

snopes.com

politifact.com

factcheck.org

truthorfiction.com

hoax-slayer.com 

urbanlegends.about.com, NO!

http://hoax-slayer.com


Faculty Voter Registration in Economics, History, Journalism, Law, and Psychology
University Facts
https://econjwatch.org/file_download/944/LangbertQuainKleinSept2016.pdf


The Truth About False News with Sinan Aral, MIT
American Universities are simply too left leaning now to even think of looking balanced ...





Many professors, universities, media sources are moderately to strongly biased toward liberal causes through story selection and/or political affiliation...


The majority of celebrities and college professors are liberal
Liberal professors outnumber conservatives 12 to 1
https://jhupbooks.press.jhu.edu/content/professors-and-their-politics

 Left Turn: How Liberal Media Bias Distorts the American Mind by Tim Groseclose

Why Judges Tilt to the Right - The New York Times



Novelty hypothesis

Crowdsourcing a Word-Emotion Association Lexicon

Word-emotion and word-polarity association lexicon quickly and inexpensively

 Even though considerable attention has been given to the polarity of words (positive and negative) and the creation of large polarity lexicons, research in emotion analysis has had to rely on limited and small emotion lexicons. In this paper we show how the combined strength and wisdom of the crowds can be used to generate a large, high-quality, word-emotion and word-polarity association lexicon quickly and inexpensively. We enumerate the challenges in emotion annotation in a crowdsourcing scenario and propose solutions to address them... more
Crowdsourcing a Word-Emotion Association Lexicon (PDF Download Available).
Available from: https://www.researchgate.net/publication/256199465_Crowdsourcing_a_Word-Emotion_Association_Lexicon [accessed Feb 2018].

Prompt word: startle

Q1. Which word is closest in meaning (most related) to startle?

•automobile

•shake

•honesty

•entertain

Q2. How positive (good, praising) is the word startle?

•startle is not positive

•startle is weakly positive

•startle is moderately positive

•startle is strongly positive

Q3. How negative (bad, criticizing) is the word startle?

•startle is not negative

•startle is weakly negative

•startle is moderately negative

•startle is strongly negative

Q4. How much is startle associated with the emotion joy? (For example, happy and fun are

strongly associated with joy.)

•startle is not associated with joy

•startle is weakly associated with joy

•startle is moderately associated with joy

•startle is strongly associated with joy

Q5. How much is startle associated with the emotion sadness? (For example, failure and heart-

break are strongly associated with sadness.)

•startle is not associated with sadness

•startle is weakly associated with sadness

•startle is moderately associated with sadness

•startle is strongly associated with sadness

Q6. How much is startle associated with the emotion fear? (For example, horror and scary are

strongly associated with fear.)

•Similar choices as in 4 and 5 above

Q7. How much is startle associated with the emotion anger? (For example, rage and shouting

are strongly associated with anger.)

•Similar choices as in 4 and 5 above

Q8. How much is startle associated with the emotion trust? (For example, faith and integrity

are strongly associated with trust.)

•Similar choices as in 4 and 5 above

Q9. How much is startle associated with the emotion disgust? (For example, gross and cruelty

are strongly associated with disgust.)

•Similar choices as in 4 and 5 above

Q10. How much is startle associated with the emotion surprise? (For example, startle and sudden

are strongly associated with surprise.)

•Similar choices as in 4 and 5 above

Q11. How much is startle associated with the emotion anticipation? (For example, expect and

eager are strongly associated with anticipation.)

•Similar choices as in 4 and 5 above

Q12. Is startle an emotion? (For example: love is an emotion; shark is associated with fear (an

emotion), but shark is not an emotion.)

•No, startle is not an emotion

•Yes, startle is an emotion

Crowdsourcing a Word-Emotion Association Lexicon (PDF Download Available). Available from: https://www.researchgate.net/publication/256199465_Crowdsourcing_a_Word-Emotion_Association_Lexicon [accessed Feb 2018].

anger
anticipation
disgust
fear
joy
sadness
surprise
trust
micro-average
any emotion

Professors and Their Politics  edited by Neil Gross and Solon Simmons

Professors and Politics: What the Research Says













Andrew Klavan & Bill Whittle: Is Christianity the Unique Essential Basis for Freedom and Prosperity?




Andrew Klavan & Bill Whittle: What is Truth?




Cynicism: Is It Deadly Dangerous or a Blessing in Desolate Disguise?






Česká novinářka zpovídala ženy džihádistů: Mezi uprchlíky vychovávají malé teroristy


Nejdřív jen ženy v domácnosti, pak sebevražedné útoky a hlavně výchova další generace džihádistů. Manželky bojovníků Islámského státu měly podle novinářky Lenky Klicperové výjimečné postavení.
S desítkou z nich v uprchlickém táboře mluvila a tvrdí, že jsou nebezpečné. Většina z nich jsou přitom cizinky a je možné, že se z uprchlických táborů už nedostanou. Jakou roli teď přesně hrají? Pomáhalo Turecko otevřeně IS? A proč je vnímání dobra a zla v syrském konfliktu naivní?
Pavel Štrunc!










national socialism
socialism