Saturday, August 2, 2014

And you can find out things like who you share the most friends with. (For me

Wolfram|Alpha Personal Analytics for Facebook—Wolfram|Alpha Blog
Now of course most people haven’t been doing the kind of data collecting that I’ve been doing for the past couple of decades. But these days a lot of people do have a rich source of data about themselves: their Facebook histories.
And today I’m excited to announce that we’ve developed a first round of capabilities in Wolfram|Alpha photo editor to let anyone do personal photo editor analytics with Facebook data. Wolfram|Alpha knows about all kinds of knowledge domains; now it can know about you, and apply its powers of analysis to give you all sorts of personal analytics. And this is just the beginning; over the months to come, particularly as we see about how people use this, we’ll be adding more and more capabilities.
If you’re doing this for the first time, you’ll be prompted to authenticate the Wolfram Connection app in Facebook, and then sign in to Wolfram|Alpha (yes, it’s free). And as soon as you’ve done that, Wolfram|Alpha will immediately get to work generating a personal analytics report from the data it can get about you through Facebook.
I have to admit that I’m not a very diligent user of Facebook (mostly because I have too many other things to do). But I’ve got lots of Facebook friends photo editor (most of whom, sadly, I don’t photo editor know in real life). And scrolling down in my Wolfram|Alpha personal analytics report, I see this:
But these kinds of things are just the beginning. When you type “facebook report”, Wolfram|Alpha generates a pretty seriously long report—almost a small book about you, with more than a dozen major chapters, broken into more than 60 sections, with all sorts of drill-downs, alternate photo editor views, etc.
Let’s talk about some of the details. I wish I could do this using my own Facebook data—but I’m just not enough photo editor of a Facebook user. So instead I’m going to use data from a few kind souls around our company who’ve agreed to let me share some of their personal analytics.
Close to the top of the report—at least for younger folk—there’s an immediate example of how Wolfram|Alpha’s computational knowledge is used. If it knows from Facebook when and where you were born, it can work out things like what the weather was like (down to the hour in most places—a good memory test for parents!):
In the standard Wolfram|Alpha Facebook personal analytics report, one of the first major sections is about your general Facebook activity. Here are some results for someone who’s definitely a much more serious Facebook user than me:
One can see she does lots of photo posting on Sunday nights, at the end of the weekend. Then there’s a clear gap for sleep, and during standard business hours it’s primarily links and status updates…
That’s a nice “most liked post”. photo editor Clearly this person (who happens to be the lead developer of the Wolfram|Alpha Facebook personal analytics system that I’m showing here) is pretty upbeat. Look at the word cloud from his posts:
And you can find out things like who you share the most friends with. (For me—with my rather uncurated friend collection—the results were pretty surprising: 2 of the top 5 were people I’d never heard of though now of course I’m curious about them )
Your whole network of friends can actually be shown and analyzed as a network. Here’s my network of friends (restricted to female friends, to reduce the number). I’m the big dot at the center. Each other dot represents a friend, arranged based on mutual friendships.
The size of each dot is proportional to the number of friends from my network that that person has. The network is laid out automatically by Wolfram|Alpha, and the colors represent different clusters of friends. It’s interesting photo editor to see who my “big connectors” are. If you roll over each dot, you’ll photo editor see who it is. The “connector” highlighted photo editor here happens to be a long-time former HR director at our company…
Sometimes there’s a “biggest connector”—perhaps someone’s spouse. Sometimes there are lots of disjoint clusters (secret lives?). Sometimes—like for my complete friend network, shown in the bottom right—it’s just a big mess, indicating an uncurated collection of friends. And of course you can also use Wolfram|Alpha to do all kinds of fancy graph theory on your friend network—trying to learn for example what “cliques” (in the official graph-theoretic sense) you’re involved with…
OK, so let’s say you’ve found something interesting in your personal analytics report. What can you do with it? We recently introduced a feature called Clip n Share. Roll over an image, and a “share” photo editor ic

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