👓 How to Teach Google What a Story Is | The Atlantic

Read How to Teach Google What a Story Is (The Atlantic)
Deep inside Google, a small team has been trying to solve a problem that's easy for any schmuck around the watercooler but frighteningly difficult for the world's most data-rich company: telling a story.

🎧 Season 2 Episode 6 The King of Tears | Revisionist History

Listened to Season 2 Episode 6 The King of Tears by Malcolm GladwellMalcolm Gladwell from Revisionist History

Revisionist History goes to Nashville to talk with Bobby Braddock, who has written more sad songs than almost anyone else. What is it about music that makes us cry? And what sets country music apart?

Why country music makes you cry, and rock and roll doesn't: A musical interpretation of divided America.

The big idea in this episode that there is a bigger divide in America that falls along musical lines more than political ones is quite intriguing and fits in with my general experience living in South Carolina, Georgia, Connecticut, Maryland, Kentucky, and California. Having been raised by a Catholic family with one parent from the city, another from the countryside, and having lived in many blue/red states surrounded by people of various different musical tastes, I do have to wonder if there isn’t a lot of value in this thesis. It could make an interesting information theoretic political-related question for research. This might be the type of thing that could be teased out with some big data sets from Facebook.

Beauty and authenticity can create a mood. They set the stage, but I think the thing that pushes us over the top into tears is details. We cry when melancholy collides with specificity.

Malcolm Gladwell in The King of Tears

He then goes on into a nice example about the Rolling Stones’ Wild Horses:

And specificity is not something that every genre does well.

This reminds me of a great quote in Made to Stick from Mother Theresa about specificity.

Mother Teresa once said, “If I look at the mass, I will never act. If I look at the one, I will.”

There’s something very interesting about this idea of specificity and its uses in creating both ideas as well as storytelling and creating emotion.

There is one related old country music joke I’m surprised not to have seen mentioned here, possibly for length, tangential appropriateness, or perhaps because it’s so well known most may call it to mind. It plays off of the days of rock and roll when people played records backwards to find hidden (often satanic) messages.

Q: What do you get when you play a country music song backwards?
A: You get your job back, your wife back, your house back, and your dog back.

The episode finally rounds out with:

If you aren’t crying right now I can’t help you…

Thanks Malcolm, I was crying…

Obama’s Secret to Surviving the White House Years: Books | The New York Times

Read Obama’s Secret to Surviving the White House Years: Books (nytimes.com)
In an interview seven days before leaving office, Mr. Obama talked about the role books have played during his presidency and throughout his life.

Not since Lincoln has there been a president as fundamentally shaped — in his life, convictions and outlook on the world — by reading and writing as Barack Obama.

Continue reading Obama’s Secret to Surviving the White House Years: Books | The New York Times

The emotional arcs of stories are dominated by six basic shapes

Bookmarked The emotional arcs of stories are dominated by six basic shapes (arxiv.org)
Advances in computing power, natural language processing, and digitization of text now make it possible to study our a culture's evolution through its texts using a "big data" lens. Our ability to communicate relies in part upon a shared emotional experience, with stories often following distinct emotional trajectories, forming patterns that are meaningful to us. Here, by classifying the emotional arcs for a filtered subset of 1,737 stories from Project Gutenberg's fiction collection, we find a set of six core trajectories which form the building blocks of complex narratives. We strengthen our findings by separately applying optimization, linear decomposition, supervised learning, and unsupervised learning. For each of these six core emotional arcs, we examine the closest characteristic stories in publication today and find that particular emotional arcs enjoy greater success, as measured by downloads.