5 Things You Won't Believe Math Can Predict

Look, we don't want to take all of the magic out of life. After all, can "science" and "mathematics" quantify something as mysterious as the beauty of music, or the evil of the human spirit, or the madness of a panicked mob?

Yeah, pretty much. Get enough data, create the best algorithm, and you can get some nice pretty graphs that tell you ...

#5. How to Write a Successful Pop Song


Music is borderline magic; great songs touch you on a spiritual level, instantly changing your mood or causing stirring memories of your youth to come roaring back. How could you ever predict whether or not people will like a song with some cold computer program? It all comes down to what's in people's hearts.

Or maybe not. We've already explained how your brain secretly loves "Call Me Maybe" due to the way "catchy" pop songs trigger an almost addictive response. You could say, "But what about the meaning of the lyrics, or the passion of the performer?" but then you'd remember that you loved "Gangnam Style" even though you had no idea what it was saying (we looked it up on Google Translate, and it looks like the song is about the time Psy got high on meth and had sex with a transvestite while riding a horse). So if it just comes down to manipulating your brain, we should be able to come up with hard data on what works.

"I don't know -- they just started playing, and all of a sudden I was married and a princess."

Scientists at the University of Bristol devised an algorithm to do just that: They analyzed songs from the U.K. Top 40 chart from the last 50 years. It takes into account 23 variables -- time signature, duration, tempo, loudness variability, etc. -- and from that they programmed software that could chew up any song and spit out the probability that it would become a hit with the public.

According to the researchers, the software has around a 60 percent accuracy rate for picking out songs that will make it to the top five and ones that won't even go above 30 on the U.K. Top 40 singles chart. That's a stunning figure, considering that it can't account for so many other variables, such as how heavily the label promoted it, or whether there was some other factor in the song's success (i.e., if the song was featured in a hit movie).

The algorithm's accuracy is also dependent on cultural context -- what worked in 1970 won't necessarily work now:

Via Scoreahit.com
Which is why the Rolling Stones have basically become the herpes of music.

You see the way the blue line is starting to shoot back up? Simplicity is coming back. "Loudness," however, is on the decline after four decades on the rise:

Via Scoreahit.com
You hear that, Enya? Now's your chance.

So, if you're a musician, take a look at the numbers and get to work. Before they find a cyborg that can do your job.

#4. Which Gang Is Responsible for a Crime


As we've previously mentioned, you'd be surprised to learn that the stupid premise behind Numb3rs, that crime show where a guy solves murders with a calculator, is basically a real thing that exists. Detectives with the LAPD collaborate with math professors to study trends in crime rates and try to predict, for example, which house in a particular neighborhood a criminal will try to burglarize next. Apparently, they can do this by essentially treating criminal behavior like traffic flow patterns, or even weather forecasting, as figuring out where a storm is going to hit apparently uses similar equations to figuring out which liquor store is going to get knocked off next.

PRO TIP: Always pick the ones that have wine without twist tops. Cork means money.

But it goes beyond simply following crime trends. That's kids' stuff. Now they've figured out a way to actually pinpoint which specific gang is most likely to have committed a particular crime. The mathematicians, led by Andrea Bertozzi, compiled a ton of data related to gang crime from Hollenbeck, one of Los Angeles' most gang-ridden neighborhoods. They painstakingly went through police records and dug up around a thousand crimes to try to understand how exactly each gang operated.

For instance, they found that 90 percent of the tag artists were extremely nearsighted.

Remember, while there are a certain number of crimes committed just for the hell of it, most of the time the criminals are doing it for a reason. This is especially true when they're members of an organization. Any organization, even an organization of high school dropouts who call themselves the East Side Skullfuckers, has goals -- they're fighting over territory, taking revenge, and so on. If you figure out what those goals are, and where they are in achieving them, you can predict what they're going to do.

So from there it was simply using the data to map out which gangs/members hated each other, who was in debt to whom, and who was overdue for a retaliation attack. When they plugged in the data for some known crimes (with the identities of the perps left out) to see if the computer could guess who actually did it, it was able to narrow down the suspects to one of three gangs 80 percent of the time (the neighborhood has about 30 gangs operating at any given time).

Including the most violent of them all, the Justice Biebers.

Holy shit, not even Batman's computer could do that. Although we can think of at least one program Bruce Wayne would find even more useful, which is the one that tells us ...

#3. Where Terrorists Are Hiding Bombs


As the last, oh, thousand years of war have taught us, winning isn't necessarily as straightforward as just blowing up all the other guy's tanks and airports. In battlegrounds such as Afghanistan, the military has to deal with guerrilla tactics, where the enemy hides within the general population. It's hard to fight somebody if you don't know who or where they are until something explodes. So how do you predict the behavior of people so desperate and/or crazy that they're willing to strap bombs to themselves if necessary? Once again, with the power of math.

The University of Maryland developed software called SCARE (Spatio-Cultural Abductive Reasoning Engine) that has been consistently able to predict the locations of guerrillas' bomb caches to within half a mile, which isn't perfect, but is infinitely better than the previous "throwing darts at a map" strategy the military was forced to employ.

"It's in one of these buildings. Go."

Because just as we saw with pop music and criminal gang scenes, hiding inside what seems like random chaos are some pretty reliable parameters. For one thing, terrorists are not likely to attack too close to home (they don't want to give away the location of their base of operations, and they're not stupid), but due to physical constraints, they're also not likely to roam too far. So right off the bat, mathematicians have a pretty good idea of what area they need to look at. But that's just the start.

The software also takes into account cultural factors such as territorial allegiances. Since different guerrilla groups may not exactly be BFFs outside of their mutual hatred of a foreign military, the areas where insurgents are active tend to be closely linked by culture or religion with the area where they keep their bomb factories.

"It's not much, but if it accidentally explodes ... who gives a crap, right?"

But this kind of thing isn't just useful for tracking down terrorists. The list of potential applications includes tracking down operating bases for criminals on home soil, as well as medical diagnosis, monitoring political organizations, and presumably tracking down the home of that dog that keeps shitting in your yard.

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