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Comment by King-Aaron | Hacker News Reader

I'm skeptical of this.

How do they ascertain that the cars belong to the suburb? Would a suburb be ranked differently if for a month there were civil works that meant a lot of contractor vehicles etc were parked up? What about if the local Ferrari club decides to go for a cruise and all meet at a coffee shop in the neighbouring suburb every week? What if the suburb was located in a cold region, where it's more practical for most people to drive a SUV in winter?

What about the republicans who drive Civics, and the republicans who drive Audis? What about the democrats that drive Toyota Tacomas, or the democrats who drive Volts?

I mean, what would it make of me? I have a toyota hilux for work, a mx5 (miata) for track days, and a subaru wrx sti for driving to the shops. I wonder what my political leaning would be considered to be?

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They ascertain nothing, they just looked at statistics.

Of course you can't assert things on a single individual based on his car. Just give a probability based on all the evidence you have.

But on a great number of people (a neighborhood) it doesn't surprise me that you get pretty good results.

They don't, your doubts are real, but...

All machine learning involves a cost function. How close do the results have to be to make a useful prediction in the context.

Certainly. My main concern is the line: "on par with some information that takes billions of dollars to obtain via census surveys"...

As soon as you have a researcher make this sort of claim, a politician will inevitably see it as "Don't spend money on census research, do this instead" ...

> What about if the local Ferrari club decides to go for a cruise and all meet at a coffee shop in the neighbouring suburb every week?

I presume they looked at more than one neighborhood? Or are you suggesting Ferrari owners have a conspiracy to do this in general?

I wouldn't put it past a group of Fezza owners to be conspiring about something at any given time :P

But to be serious, my point was more about the way that they are collecting their data. If you were focusing on buildings and structures in a suburb to rate demographics, I would think that you would have more accurate results. Cars don't stay still though, and just because it's in a location at a particular time doesn't necessarily mean it lives there. The ferrari club going for coffee is just an example of affluent (types of) cars possibly throwing out results.

It's doesn't mean anything to just point at the source of an error though. You need to show that the error results in a bias (edit: or variance) on a large scale. My point here was that it seems pretty plausible for the law of large numbers to take care of little variances like this, so if you want to claim their collection was problematic, explain which errors could occur consistently so as to reach a wrong conclusion.

> Or are you suggesting Ferrari owners have a conspiracy to do this in general?

Maybe their conspiring is the reason they got their Ferraris in the first place ;-)

You don;t have to look at the cars, you just need to look at the database of registered owner/drivers.

Those are edge cases. Nothing says that this will be accurate for every individual block 100% of the time, but for most neighborhoods, the correlation between car type and political leaning appears strong.

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