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Zook discovered that the quake’s emotional epicenter was just northwest of the seismic one, in Hazard, Kentucky, and as simple as it sounds, this kind of finding is truly new.
This data above does not prove that the Mountain Time Zone is one big high-plains makeout party. In fact, the explanation is rather banal: if you are looking for people to have sex with in a place like Pierre, South Dakota, your local options are limited. So you try a dating site to find what you want. It’s simple selection bias in our data, but there’s meaning there: where people can’t find satisfaction in person, they create alternative digital communities. On a dating site, that means communities with similar sexual interests.
They lay it down right there on the label—“England’s first registered trademark.” But what they don’t tell you is that Bass was only first because a brewery employee happened to be first in the queue at the registrar’s office the morning that Britain’s Trademark Registration Act took effect.
His article, really more of a sales pitch, asks readers to first determine their “feature-benefit model” and then to relentlessly market it to employers, coworkers, and the larger world … or else! Those are literally the last two words, and they punctuate all the typical hokum (“Sit down and ask yourself … what do I want to be famous for? That’s right—famous for!” and “You are a leader. You’re leading You!”) that the worst business writing has to offer.
Fake it till you make it.
On the left you see the kinds of simple, fleeting concerns you’d expect from people on Twitter. On the right you see almost entirely management jargon: if you have a lot of followers, you are in fact much more likely to speak like a corporation.
and those institutions don’t follow them back. The mainstream culture of the service is organized around that one-to-many communication, organized, in fact, around the brand. But black users tend to focus on personal use and are highly reciprocal—hence high-follower counts and the enhanced ability to launch memes to the top of the charts.
Its most precious resource, followers, is distributed far more unequally than wealth. In my sample, the top 1 percent of accounts has 72 percent of the followers. The top 0.1 percent has just over half. It is much, much harder to get to a million followers than it is to make a million dollars. There were 300,890 people who reported over $1 million in income to the IRS in 2011. Right now there are 2,643 Twitter accounts with 1 million followers, worldwide. Perhaps half are in the United States. Being an American with 1 million Twitter followers is roughly equivalent to being a billionaire.
Klout is one of the leading personal analytics firms; they look at all your social media accounts and, through a little proprietary black magic, give you an all-in measure of your online influence, 0 to 100. You’ll remember per Montoya (and Carnegie): influence is what a personal brand is all about, and Klout helps you figure out how you’re doing. Right now, my Klout score is a fairly pathetic 34. TeamFollowBack comes in at 60, which makes me want to either laugh or cry. On the one hand, these people have gotten the equivalent of a D– grade on their only reason to exist. On the other, they
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Imagine a mysterious die—you can’t count the sides but you can roll it and see what comes up. Roll once and you could get any number, you learn nothing. Roll it a bunch of times, you get the distribution, you get the average—and that defines the die right there. You know the shape only through aggregation.
On the other hand, every number in this book has many hundreds, often many thousands, of people behind it, none of them famous. Here’s the kernel of it: the phrase “one in a million” is at the core of so many wonderful works of art. It means a person so special, so talented, so something that they’re practically unique, and that very rareness makes them significant. But in mathematics, and so with data, and so here in this book, the phrase means just the opposite: 1/1,000,000 is a rounding error.
Data takes too much of the guesswork out of the sell. It’s a rare urban legend that turns out to be true, but Target, by analyzing a customer’s purchases, really did know she was pregnant before she’d told anyone.
In some ways, that kind of corporate intrusion is better than brands actually trying to “relate.” Last summer, a Jell-O marketing campaign co-opted (tagjacked?) the hashtag #fml, which is Internet shorthand for “fuck my life.” Their social media people began responding to tweets that contained the tag with an unsolicited offer to “fun” the person’s life instead, with coupons. Thus people in extremis received jaunty offers from a gelatin, as in this exchange: Pyrrhus Nelson @suhrryp Seeing my bank account disappear at the dr office #fml JELL-O @JELLO @suhrryp Fun My Life? Of course we will. In
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If employers begin to use algorithms to infer how intelligent you are or whether you use drugs, then your only choice will be to game the system—or, to borrow the wording from the previous chapter, “manage your brand.”
Apparently, one of the strongest correlates to intelligence in the research was liking “curly fries.” Who could reverse-engineer that?
We make calculated trades all the time. Public figures sell their personal lives to advance their careers. Anyone who’s booked a hostel in Europe or bought a train ticket in India has had to decide if the private room is worth the extra money. And not to confuse the issue here, but many people, men and women, trade on privacy when they walk out the door in the evening, giving it away, via a hemline or a snug fit, for attention. So the exchange isn’t new.
found out that a site called geni.com is well on the way to creating a crowdsourced family tree for all mankind.
Soon the half measures provided by menu options as you “manage your privacy settings” will give no protection at all, because the rest of your world won’t be so withholding. Companies and the government will find you through the graph. This whole debate could soon be an anachronism.
