Another Data Miner Finds Love Online: It’s Not Why You Think

So, this happened:

http://www.wired.com/wiredscience/2014/01/how-to-hack-okcupid/all/

But the title of the article isn’t exactly true: “How A Math Genius Hacked OKCupid To Find True Love”

He did devise clever bots and algorithms — he is a math genius, after all — and employed 12 fake profiles for his data scraping (not unlike Amy Webb). And he used his data to help him make his profile appear more compatible to certain groups of women.

But here’s the kicker: He did not “find” love that way.

The woman he ended up finding love with, and proposing to, was not in his data set.

She found him.

She contacted him first. (Like a rat!)

For me, this is a major takeaway of this story, as I generally advise my female clients to go ahead and make the first move.

My second takeaway is: I like how he used the data responsibly and thoughtfully.

When he created his two uber-profiles, he was careful to be honest. He was truthful in the OKC quiz questions he answered, using his research only to help him determine which questions to answer and how important to say each question is. One of his ideal types preferred teachers. He played up (but did not make up) his teaching experience. His other ideal type was more artsy and for that data set, he posted a picture of himself playing guitar.

How this relates to what I do:

When I work with clients, we look at who they are, and whom they are attracted to, in order to help determine what goes into their profile, how they choose to communicate about themselves in a way that will connect with their desired potential partner.

I am against the use of matching algorithms for a variety of reasons, so I do not recommend using dating sites that rely solely on them. However, like Chris McFinlay, my clients who use OKCupid end up revising their OKC questions and answers in order to change up what the system “thinks” is a good match for them.

Possibly my favorite unexpected finding in this experiment is how the women he liked fell into distinct clusters. To me, this shows how we as humans are infinitely unique and yet not. We sort ourselves culturally, by experience, even by markings (tattoos), almost like breeds of dogs:

“… he noticed latent variables emerging. In the younger cluster, the women invariably had two or more tattoos and lived on the east side of Los Angeles. In the other, a disproportionate number owned midsize dogs that they adored… McKinlay’s code found that the women clustered into statistically identifiable groups who tended to answer their OkCupid survey questions in similar ways. One group, which he dubbed the Greens, were online dating newbies; another, the Samanthas, tended to be older and more adventuresome.”

(This leads to a longer discussion around how there might not be just one “The One” or even just a few “Ones” but rather a large swath of “Ones” — out of whom we each find “A One” based on where we are in our mutual life paths, our emotional availability in that moment, geography, luck, and/or destiny.)

The graph below shows how the groups he identified answered four specific questions. (Click on the image to view the questions and the color key in the article.)