51–60 of 86 posts
As a marketing term - sure, that would be a good indicator of interest. Since this article is more scientific than marketing-oriented, I would clarify what some of the metrics mean (or don't mean).
Excellent, fantastic visualizations though!
How is it possible that Facebook, which owns the data, does not give tools like these but others tap this using their data?
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The attitude of companies like Facebook, Google, Twitter is: if the product isn't addictive or useful to Billions of people, its not worth doing. Hence there are vastly more resources dedicated to assimilating eg photos and games into their ecosystem, than into something computationally innovative. This is IMHO a huge mistake, since they could instead be introducing simple forms of programming that takes you on a con…
I'm sure Facebook's Data Science team does a lot of interesting things internally. They do in fact have some interesting papers [0] and [1], though obviously with more of an 'academic' feel than the blog post. [0]: http://arxiv.org/abs/1111.4503 [1]: http://arxiv.org/pdf/1201.4145 (edit) Edit: they also have this FB page which has a steady stream of interesting stuff: https://www.facebook.com/data
One thing that bugs me is how comments are linked to "interest". There are many topics that interest people (passive consumption), that do not necessarily translate into engaging in a conversation with others publicly. As a marketing term - sure, that would be a good indicator of interest. Since this article is more scientific than marketing-oriented, I would clarify what some of the metrics mean (or don't mean). Exc…
I found this interesting. What I would love to have seen, however, is a probe into the dynamics. You did a nice abstraction over time as you measured property X as age was varied. I would have loved to have seen the manner in which topics and ideas spread over your network. For instance: If an event occurred in New York, say, how long would it have taken to spread to San Francisco? If there were no progression, topic…
Interesting points. 1. Dynamics You're right, that would be very interesting. The most obvious way we could have done this is by looking at the spread of our app itself as people started to use it. Unfortunately, we only started recording anonymized stats for the second release, so we've somewhat missed the boat there. To do it with links and general "memes" would be technically much harder, because we'd have to peri…
It goes some way to answering the dynamics question.
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I'm sure Facebook's Data Science team does a lot of interesting things internally. They do in fact have some interesting papers [0] and [1], though obviously with more of an 'academic' feel than the blog post. [0]: http://arxiv.org/abs/1111.4503 [1]: http://arxiv.org/pdf/1201.4145 (edit) Edit: they also have this FB page which has a steady stream of interesting stuff: https://www.facebook.com/data
Thank you so much. Edit: I don't work at facebook.
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Is there a description available of the algorithm used to generate the 'cluster diagrams'? Really nice work.
Thanks! Some of the plots use this: http://reference.wolfram.com/mathematica/ref/CommunityGraphP... The underlying community detection uses: http://reference.wolfram.com/mathematica/ref/FindGraphCommun... If you look under "Method", there are a bunch of different methods to use that I'm told correspond to various landmark papers in the field. If you know about community detection, you'll recognize which methods corre…
All the more so because Jeff Hammerbacher is often credited with coining the term "data science", and he started doing it at -- that's right -- Facebook.
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Thanks! Some of the plots use this: http://reference.wolfram.com/mathematica/ref/CommunityGraphP... The underlying community detection uses: http://reference.wolfram.com/mathematica/ref/FindGraphCommun... If you look under "Method", there are a bunch of different methods to use that I'm told correspond to various landmark papers in the field. If you know about community detection, you'll recognize which methods corre…
I found the methods very interesting and thanks for the work. Have you thought to add the Surprise method? http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjourna... It appears to solve the resolution limit of modularity.
Introducing "data science for Facebook" in 2013 is ... odd. All the more so because Jeff Hammerbacher is often credited with coining the term "data science", and he started doing it at -- that's right -- Facebook.
Didn't know Jeff Hammerbacher coined "data science" at Facebook -- that's interesting!