Various friends—at random it seemed—had mentioned Downton Abbey to me—some were colleagues, others were friends from various social circles. I say “at random” because these various friends had nothing in common with each other except that if they ever met each other I’d be their mutual friend. I was the common denominator, the connection, the line between two points.
Then the pastor at my church used Downton’s butler, Mr Carson, to illustrate a point. That was when I decided I needed to see this show. So I put it in my Netflix queue. After I had sent the first disc back, I made short order of cornering a coworker and asking if I could borrow the whole first season. He owned it.
That’s how I met Downton Abbey.
I added Breaking Bad to my Netflix queue.
These seeming coincidences are a delightful part of life. And part of the curiosity is finding the geometric plane that intersects all these points: me, various friends, Downton Abbey, and Breaking Bad. I want to unearth the commonalities—in people, plot, style, story, or whatever else—that might clue me in to why these two shows come up together in conversation. These connections, this plane, has some sort of shared characteristics, and I want to know it.
I thought of these recent serendipities when I read Technology Review’s August 2012 cover article “What Facebook Knows.” In it, Tom Simonite looks at Facebook’s “Data Science Team.” He describes them as the Bell Labs of the 21st century. The team conducts social experiments using data from Facebook’s 900 million users. Unprecedented. Not only that, but they are especially interested in the 69 billion connections between these users. Billion. And these connections include people like me and other data points like Downton Abbey and Breaking Bad. What is the plane that intersects all these points?
Not only does Facebook want to find that plane, they also want to harness that knowledge. Facebook’s Data Science Team wants to understand how my connections compelled me to start watching Downton Abbey, and then how other connections led to Breaking Bad after that. Simonite writes in TR that a member of the Data Science Team
“found that our close friends strongly sway which information we share, but overall their impact is dwarfed by the collective influence of numerous more distant contacts—what sociologists call ‘weak ties.’ It is our diverse collection of weak ties that most powerfully determines what information we’re exposed to.”
In other words, if Facebook can find these planes of common interests and harness acquaintances who are already talking about them, then Facebook can engineer the serendipities that their advertisers would pay for. Facebook will be able to replicate my serendipities with Downton and Breaking Bad. And they will be able to sell this power to advertisers.
Perhaps this sounds conspiratorial, but Facebook relies heavily on advertising to make money. 85 percent actually. Or about 850 million dollars in 2011. If they can make their advertising more effective, it’s in their interest to do so. If Facebook can engineer serendipity, it will pay off.
Now some people like to say that everything happens for a reason. And though I might nuance it more and prefer to phrase it differently, I probably ascribe to the gist of that belief. But what those reasons are exactly and whose reasons we’re talking about is unclear. But with Facebook’s Data Science Team and the research its doing, the answers might soon be money and corporations. If they aren’t already. As for Tennessee walking horses, I’m still working on that one.