Dating data blog

” Users are matched based on the overlap of their answers and how important each question is to both users.Yagan said data was built into the business model from the beginning.

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Free onlone local sex chat no sighn - Dating data blog

In 2010 Christian Rudder, one of the founders of OKCupid, started a blog to accompany his massively popular dating site.

Called OKTrends, it was an under-the-hood look at the vast amounts of self-reported data he and his colleagues had access to as the administrators of a site where millions of people answered extensive questionnaires, filled out in-depth profiles, and messaged potential partners.

calculates the relationship between "percentiles of attractiveness" and how many friends a Facebook user has. Rudder has also compiled maps showing where Craigslist missed connections are most likely to occur, state-by-state. We’re divided by class, which correlates with geography. He cites Naomi Klein’s Rudder is excited by the idea of being able to see, as the book’s cover says, how we behave "when we think no one is watching" — a world where data collection doesn’t occur in a lab, but in the channels of the internet where participants are free from self-consciousness. The subtext, though he never quite goes out and says it, is an idea that’s held by many in the tech industry: we’re living through the democratization of information, in this case of hard data.

It tells us that Twitter users with more than 1,000 followers use a lot of corny marketing words like "marketing" and "tweetup." We learn that when you compare the words most commonly used on Twitter with those used in the English language elsewhere, Twitter users write "love" and "today" with far more frequency. In New York it’s the subway; in Texas it’s Walmart; in Southern California, the gym. But buried in the back of the book, in Rudder’s notes about the data-collection itself, we learn that the author gathered most of his information through a combination of buddy-to-buddy and business-to-business interactions with the people behind the companies who collect it, an admission that doesn’t do much to dissolve the vision of Silicon Valley as an exclusive foosball-peppered frat lounge.

“Then we can model the kinds of conversations on the site that lead to an in-person meeting.” Ok Cupid can currently track the five million messages sent every week on the site as well as other revealed preferences, like ratings of profiles.

According to Yagan, Ok Cupid doesn’t use sophisticated data mining or analytics tools: “Most of it can be done by querying the database and crunching numbers in Excel.

We just tell you that if you use a flash you’ll look seven years older.” I asked Yagan about the data on which Ok Trends draws. “Then we have stated preferences; the answers that people give to the questions we ask them.

We use that kind of data occasionally, but it’s not the core difference that we have.

Our approach to dating isn’t that there’s some psychological theory that will be the answer to all your problems.

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