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On the sidebar where my “Personality Snapshot” is broken down in further detail, a section called “Chat-Up Advice” advises, “Do your best to avoid being negative. Get to the point quickly and don’t waste their time. They may get impatient if you’re moving too slowly. ” I’m a catch. Instead, it’s paired with the language processing company to compute the compatibility between me and its user base using the contents of our Twitter feeds. Is this good matchmaking or a gimmick? As a sex-crazed neurotic, I think you know where I stand. Dating apps promise to connect us with people we’re supposed to be with—momentarily, or more—allegedly better than we know ourselves.

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Sometimes it works out, sometimes it doesn’t. But as machine learning algorithms become more accurate and accessible than ever, dating companies will be able to learn more precisely who we are and who we “should” go on dates with. How we date online is about to change. The future is brutal and we’re halfway there. Today, dating companies fall into two camps:

sites like eHarmony, Match, and OkCupid ask users to fill out long personal essays and answer personality questionnaires which they use to pair members by compatibility (though when it comes to predicting attraction, researchers find these surveys ). Profiles like these are rich in information, but   they take time to fill out and give daters ample incentive to misrepresent themselves (by asking questions like, “How often do you work out? ” or “Are you messy? ”). Tinder populates profiles with Spotify artists, Facebook friends and likes, and Instagram photos.

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Instead of matching users by “compatibility, ” these apps work to provide a stream of warm bodies as fast as possible. It’s true that we reveal more of ourselves in Twitter posts, Facebook likes, Instagram photos, and Foursquare check-ins than we realize. We give dating apps access to this data and more: when one journalist from asked Tinder for all the information it had on her, the company sent her a report 855 pages long. Sound creepy?

Maybe. But when I worked as an engineer and data scientist at OkCupid, massive streams of data like these made me drool. In the future, apps like Tinder may be able to infer more about our personalities and lifestyles through our social media activity than an eHarmony questionnaire ever could capture. Researchers already think they can predict from our Foursquare check-ins, whether or not we’re depressed from and, and how intelligent, happy, and likely to use drugs we are from our. One 7568 study from Cambridge University that analyzed the connection between Facebook likes and personality traits found the biggest predictors of intelligence were liking “Science” and “The Colbert Report” (unsurprising) but also “Thunderstorms” and “Curly Fries.

” That connection might defy human logic, but what does that matter if you’re feeding a personality algorithm into a matchmaking algorithm? Because indicators of our personality can be subtle, and we tend not to curate our activity on Facebook as closely as we might a dating profile, perhaps there’s more integrity to this data than what users volunteer in survey questions. “My initial reaction to online dating is that people might present a version that’s unrealistic, ” said Chris Danforth, Flint professor of Mathematical, Natural, and Technical Sciences at the University of Vermont who’s studied the link between Instagram, Twitter, and depression. “But what seems to be revealed every time one of these studies comes out is that it looks to be the case that we reveal more about ourselves than we realize, maybe not as much in solicited surveys but in what we do. Someone’s likes on Facebook could be a better predictor of whether they would get along with someone than survey answers.

”The data could also be used to keep users honest when they’re making their accounts. “I think it would be interesting if OkCupid called you out as you’re filling out your profile, ” said Jen Golbeck, a researcher who studies the intersection of social media and information at the University of Maryland.

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