How Facebook is working to engineer coincidence

I started watching Downton Abbey this spring. It’s “Downton,” not “Downtown.” I know. I made the same mistake. And there are no abbots as of season two, episode six. But I do watch it religiously. Here’s how it started.

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.

This is not to say that they wouldn’t have other things in common, but only that they didn’t actually know each other. In fact, they did have something else in common: Downton Abbey. And these two connecting lines—me and Downton Abbey—really made me start to wonder, “What do I have in common with Downton Abbey?” If only one line runs through any two points in space, why were Downton Abbey and I on the same line? And why did we both connect those 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.

Since then, I’ve rounded up a group of friends (mostly women, which does not bother me) to watch the second season. While I was recruiting, something odd began happening. I would be talking about Downton, and my prospective recruits would come back with, “Oh, have you seen Breaking Bad?” After the third conversation like this, again with random points in space, I began to wonder, “What’s the connection between a British period drama (that borders on soap opera) and a modern American drama about a science teacher-turned-meth dealer?” So I did what any rational person would do.

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.”

If the producers of Breaking Bad can expose me to my acquaintances who like Downton anytime they mention Breaking Bad, then the producers have a pretty good chance that I’ll watch Breaking Bad.

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.

With Facebook’s research, advertisers will be able to “powerfully determine what information we’re exposed to” and motivate our purchases in ways that “dwarf” the influence of our close friends. Not coincidentally either. Simonite believes, “Facebook might eventually be able to guess what people want or don’t want even before they realize it.” This sounds a lot like Google’s Eric Schmidt in an interview with the New York Times, “I actually think most people don’t want Google to answer their questions; they want Google to tell them what they should be doing next.” It sounds like, with what Facebook knows, this may very well be possible.

This past spring I had another seemingly random experience. I was navigating a real-life dictionary, with pages and all, looking for some word or another, when I ran across the entry “Tennessee walking horse” complete with an illustration. I didn’t give it much thought until, driving home that day from work, I found myself at a stoplight, behind an SUV with a license plate frame that read “I Heart Tennessee Walking Horses.” Now I don’t live in Tennessee. I live in Illinois. And the suburbs are no place for horse farms. To that point in my 30 years of life, I’d never heard of Tennessee walking horses. I believe this is a commentary on their obscurity and not my ignorance. But being exposed to Tennessee walking horses twice in the same day couldn’t be ignored.

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.