When I give the dating app LoveFlutter my Twitter handle, it rewards me with a 28-axis breakdown of my personality: I’m an analytic Type A who’s unsettlingly sex-focused and neurotic (99th percentile). 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.
Loveflutter, a Twitter-themed dating app from the UK, doesn’t ask me to fill out a personality survey or lengthy About Me (it caps my self-description at a cute 140 characters). Instead, it’s paired with the language processing company Receptiviti.ai 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. 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 dubious). 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?”).
On the other hand, companies like Tinder, Bumble, and Hinge skip surveys and long essays, instead asking users to link their social media accounts. Tinder populates profiles with Spotify artists, Facebook friends and likes, and Instagram photos. Instead of matching users by “compatibility,” these apps work to provide a stream of warm bodies as fast as possible.
“Regarding what we learned, we had some disturbing results that I do not want to share. They were quite offensive.”
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 The Guardian asked Tinder for all the information it had on her, the company sent her a report 800 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 how neurotic we are from our Foursquare check-ins, whether or not we’re depressed from our Tweets and the filters we choose on Instagram, and how intelligent, happy, and likely to use drugs we are from our Facebook likes.
What’s more, the relationship between our online behavior and what it implies about us is often unintuitive. One 2013 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?