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Google's Experimental Newsroom Avoids Negative Headlines
theodp writes: After Brazil's dramatic World Cup defeat by Germany, writes NPR's Aarti Shahani, Google's experimental newsroom focused on search trends that didn't rub salt in Brazil's wounds, choosing to not publish a single trend on Brazilian search terms. Copywriter Tessa Hewson said they were just too negative. "We might try and wait until we can do a slightly more upbeat trend." It's a decision that puzzles Shahani, but producer Sam Clohesy explained, "a negative story about Brazil won't necessarily get a lot of traction in social." In old-school newsrooms, if it bleeds, it leads. But because this new newsroom is focused on getting content onto everyone's smartphone, marketing expert Rakesh Agrawal says, editors may have another bias: to comb through the big data in search of happy thoughts.
Thank you Google for protecting me from reality no one should have to know about bad things that happen, in fact, why should we know anything at all except for Google approved happy thoughts. Every year Google seems to do something that makes me hate them more and more. So fuck you Google - you're a bunch of authoritarian asshats who think you should control the information we have access to while trying to turn everyone into your personal little database to mine and sell info from. Just go fuck yourselves.
I don't want upbeat headlines. I want the news.
That will include good and bad headlines.
This sounds like a stupid idea, only tell people the upbeat things and let them live in blissful ignorance of what's actually happening in the world. The world doesn't work like that.
What next, not telling us when governments misbehave, or when some atrocity happens so we don't all get sad?
Lost at C:>. Found at C.
Worse than that. It's like Brave New World news. The only things fit to publish are the things that keep us happy(and thus amendable to advertisements in this case). It's not trying to make on specific entity look good, it's trying to engage in actual mind control via selection bias.