Stuff Harvard, MIT, Stanford & Caltech People Like

[dm8]

Berkeley, sadly, is perhaps too large and diverse for an overall characterization.

So true. As a Cal alum, I think he is spot on here. :-)

I pulled about 400 followers from each school, and added a couple filters, to try to ensure that followers were actual attendees of the schools rather than general people simply interested in them

How did he ensure followers were actual attendees of the schools programmatically? It would be really hard to find out this type of information. And can be considered as borderline creepiness in some cases.

EDIT: He also works as a data scientist at Twitter. So I'm sure he has access to lot more internal data rather some sort of mashup between Twitter, FB, LinkedIn APIs.

[aggie]

How did he ensure followers were actual attendees of the schools programmatically?

He mentions in the comments "I basically just checked that they didn't follow any other schools (from a small list). It's certainly not the greatest filter, but it did seem to work for a small number of people I hand-checked."

[oraj]

400 people might not be a lot to go through if you have lots of spare time on your hands.

[ScottBurson]

Interesting. Would also like to see p(topic|school=X).

[ballooney]

Well, god gave us Bayes' rule for a reason.

The article does not point out that sampling quora users might not be (I would say is probably not) an unbiased estimator of the the students of these places as a whole. Quora attracts a certain kind of person, I've never seen it mentioned anywhere outside of techy startup / valley circles. Maybe that's implied by virtue of it being in the HN ecosystem, but still it should be explicitly stated as a flaw in the method. Lies, damned lies and statistics etc.

[rjtavares]

MIT and Stanford like Hip-Hop Music. I'm pretty sure MIT prefers Biggie and Stanford prefers Tupac (note: this has nothing to do with east/west coast, but rather pure skill vs. charisma)

[carlob]

Interesting, but wrong use of conditional probabilities. All OP is saying is that the frequency of people from school x following topic y is p.

The dataset is just not the right one to say that P(x|y) = p, because of, say, all the people who follow food in NYC and go to NYU which were not taken into account here.

[sesqu]

Surprisingly diverse interests, considering the huge bias in the dataset (public quora profiles). Well worth reading, though I was left wondering about the inverse probabilities.

[sadga]

Article title should be "Reverse index of where people went to school who talk about various topics".

Obviously, the author chose a more wieldly title, but a far less correct wrong.

[romain_g]

Taylor Swift ?

[probably]

Dude Taylor Swift is awesome. I can relate.

But good eye on that. ;)

[bitwize]

Yeah, how did she score higher than Daft Punk?

[wilfra]

"Berkeley, sadly, is perhaps too large and diverse for an overall characterization."

That isn't sad at all. It's great. As a UC grad, the diversity of the student body was one of the absolute best things about my college experience. Do I wish I went to Harvard or Stanford? Sure, but not for their homogeneous student bodies.

Otherwise, pretty interesting read.

[echen]

It was a tongue-in-cheek comment :) -- sad from the perspective of me trying to find a cute pattern for Berkeley.

[baritalia]

Interesting thing to read while sipping your morning coffee but that's it, really.

[nuttendorfer]

Which is just what I did. Nothing wrong with that.

[yen223]

Not every article has to be a profound, life-changing one :)