FakeNews (Junk News or yellow journalism) is when legitimate stories or facts are suppressed, journalistic standards aren't adhered to, half truths are told, or a narrative spun to where the story becomes misleading or false. Think: manufactured crises, hoaxes, clickbait (sensational teasers/headlines with buried facts), bias or selective fact-checking, anonymous or paid sources, minor stories obscuring more significant news, delaying or ignoring newsworthy events, are all forms of FakeNews. Most retractions or corrections are evidence of shoddy standards and/or editorial bias creating FakeNews. Some of their FakeNews includes: 6 items
- 2019.03.20 FOIA Requests - Biased News is Fake News, as is having different standards based on party. So a real Journalist (Brent Scher at Free Beacon), just did a simple thing: compared FOIA (Freedom of Information Act) requests to the EPA to see how many times media outlets fact checked or investigated Obama versus Trump. NYT did 4x as many request in Trump's first year, as Obama's entire last term. WaPo: went from 1 request for Obama's last term to 43 in Trump's first 2 years. Politico: 15 to 198. CNN 25 to 47. Buzzfeed: 18 to 38. ABC: 4 to 32. This is evidence of a double-standard that the observant have known about for decades.
- 2019.02.23 Tuckergate - BuzzFeed FakeJournalist (KateAurthur) tries to gotcha Tucker Carlson by double-tweeting of a picture of a sex worker trying to kiss him on the cheek. And one of the attendees explains the context Dennis Hof's wake, Tucker is laughing and pulling away, and had no idea what her profession was. Oh the humanity. A journalist would have called for comment before posting.
- 2019.01.27 Learn to Code - ❄️ The left is angry because after the Obama administrations anti-business/anti-coal policies put many (10's of thousands) out of work, the reply by media outlets like NPR, Wired, NYT against the cries of anguish was, "Learn to Code" (the meme trended starting in 2011-2015). Implying lifetime coal miners or manufacturers targeted by the lefts policies, could just get retrained, and get new jobs in the tech sector. Well, last week, massive layoffs hit HuffPo, BuzzFeed, and Gannett News, hitting a small fraction as many workers as under Obama. And since turn-about is fair-play, some reflect the "Learn to code" information right back at the newly unemployed's cries of how life is unfair. The left had a melt-down calling their own message a hate meme (as did Twitter), but only when their sentiments were directed back at them. "How insensitive and cruel". Ya think?! If they were self-aware, they'd be getting a very important life-lesson from this, but instead they're too busy banning things that hurt their feelings to learn.
- 2019.01.17 Impeachment - Buzzfeed released an article that said Trump had ordered his Attorney (Michael Cohen) to lie to investigators, which set off the Democrats impeachment Tourettes again. ("Get the noose!") Nevermind that: it was implausible, from an unreliable author and publication, with anonymous sources, and made no sense -- the left and their media was all over it, and Congress was already demanding an investigations: which forced Mueller to release an unprecedented statement (during an investigation), that said the story was bullshit. And the left-press was crestfallen over the truth.
- 2017.02 Trumps ExecOrder cause a Woman's Death - CNN's Erol Lewis pushed a false story that Trump’s Executive Immigration Order caused Michigan Woman’s Death, after the story had already been disproven. If they retracted and apologized, they might not be known as FakeNews.
- 2017.01.10 Fake Dossier - Most media outlets (besides BuzzFeed) avoided the salacious Steele (Pee Pee) Dossier. But once it ran, plenty (NYT, CNN/Evan Perez, MSNBC, NBC, etc), republished it and/or jumped on board to talk about it, and not refute its abusrdity, or clarify its provenance as a dirty/corrupt election trick (created by the DNC) and used to get illegal warrants and undermine our democracy. Instead CNN/BuzzFeed used it to infer that Trump had Russian ties (collusion), or was compromised and other FakeNews.