Nate Silver looks to 2014

Star forecaster Nate Silver, fresh from this month’s election, predicts the House of Representatives in 2014.

Unlike the presidential race, this early forecast doesn’t rely on polling.  Instead Silver looks to historical patterns.


Extrapolating the future of computer hardware

Here’s a good example of the extrapolation method, applied specifically to computer hardware.  Feld provides many examples, some tutorials, and finally offers caveats.

(via the LinkedIn Predictors group)

Influencing a prediction market

Skewing a prediction market: somebody plunged a lot of money into Intrade’s US presidential election market right before voting day.

At around 3:30 pm, I noticed that the order book for both Obama and Romney contracts on Intrade had become unusually asymmetric, with a large block of buy orders for Romney in the 28-30 range, and a corresponding block of sell orders for Obama in the 70-72 range.

Why that combination?

If one really wants to manipulate a market, it has to be done by placing large orders that serve as price ceilings and floors, and to do this across complementary contracts in a consistent way.

The hundreds of thousands of dollars spent (!) didn’t seem to have an effect.  But they could have.

Predicting movie ticket sales through Wikipedia edits

How can we use big data to grapple with the future?  An intriguing new paper presents a new take on this question, using Wikipedia edits to forecast movie box office.  “Early Prediction of Movie Box Office Success based on Wikipedia Activity Big Data” (Márton Mestyán, Taha Yasseri, János Kertész)(pdf) shows a model owing much to previous efforts relying on Twitter mentions, but moving in a different direction.

We show that the popularity of a movie could be predicted well in advance by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia.

Note that this is a contextual approach, not based on the actual content of a movie (“the Wikipedia model does not require any complex content analysis”).

The maths go over my head, which reminds me to do some studying.

One minor note: I like the way they define rigor.

(via Technology Review)