成人快手

In the final stages of a six-year PhD, Chris was spending almost 24 hours a day at work.

“I had a little foam pad that I would roll out under my desk to sleep, and I would go to the UCLA gym to take a shower,” he recalls

But with non-stop studying taking its toll, Chris had decided he wanted more from life and signed up for online dating.

The only problem was, hardly anyone was seeing his profile

In nine months, Chris had matched with fewer than 100 women.

“I probably was not the top hit, even for someone in LA who was searching for nerdy guys, six feet tall with blue eyes. I probably wasn't anywhere near the top.”

So, he decided to game the algorithm.

Chris knew if he could figure out the system, he could beat it

“If I can just maximise my search ranking and the results to any search that's run, what if I could actually reach the top of every single search?” Chris wondered.

The site calculated matches based on people’s answers to thousands of multiple choice questions. But Chris realised that if you didn’t answer the right ones, it would limit your matches.

“Ninety-eight per cent of the questions only had maybe ten people answering them. But there were a few questions that almost every single person answered.”

So, to get more dates, Chris needed to answer the right questions in the right way.

His digital minions had just one mission: “To create profiles, gather data and then delete themselves.”

By building thousands of fake profiles each answering different combinations of questions, Chris could gather crucial data on the kinds of women they matched with.

“I was probably in violation of the Computer Fraud and Abuse Act. I had no idea about any of that. I was just like, ‘Well, whatever. The information's online, I'll just go get it.’”

Chris collected data from 20,000 women across LA

Over six weeks and more than 200 hours, Chris scraped six million question and answer combinations from the site.

He then fed the data into a computer programme he’d used for his PhD to produce a multidimensional graph. His hope was that it would reveal a collection of women who were perfect for him.

And it did: of seven clusters of data points on the graph, Chris focused in on a group of creative women who seemed to be just who he wanted to meet.

Now, he had to get the women he liked to notice him

Chris created a new all-star profile, with answers that matched everything these women were looking for.

“The only things I could really control were which questions I answered and how I answered them”, Chris says. “But… I had access to about a thousand questions optimised for each of these clusters of like-minded people.”

“I wasn't really prepared to sort through all the human consequences”, Chris admits. But he decided he couldn’t stop now.

“I was so shocked that I’d actually managed to solve the problem, I was therefore obliged to engage in the IRL [in real life] portion of this odyssey.”

Chris decided to go on one date a day. He started out opting for posh dinners and romantic strolls, but soon ended up at wild parties. “I burnt out after maybe a month of four or five nights a week going on serious dates.”

By his 88th date, Chris wondered whether it was time to stop

But then Christine Tien Wang walked in. “I could tell immediately she's extremely competitive and ambitious... I was infatuated by that,” he recalls.

“I don't want to say it was love at first sight, but it was like a very strong magnetic attraction, very early.”

And now? “We've been happily together for almost 11 years and… life is good.”

Mathematician Hannah Fry’s Uncharted reveals the amazing insights and outlandish true stories that can be hidden behind the lines, dots and data on a graph. Listen to the full series now.