Editorial Notebook

Tinder measures desirability

Since its release in 2012 as an online dating app, Tinder’s popularity has skyrocketed, with a reported 1.4 billion swipes per day and 2.4 million matches per day (https://poly.rpi.edu/s/qc11z), The app is popular for good reason, it gives users the safe feeling of not having to face rejection, combined with a simple concept; if you like someone, swipe right, if they swipe right too, you can talk, eliminating the often all-too-real struggle of trying to interact with people face-to-face. Picture trying to figure out how to introduce yourself to that someone who catches your eye—you design the perfect introduction in your head, carefully plan conversation topics, jokes, and witty lines. You decide to approach them, your heart rate speeds up as you walk up to them, you panic, make quick eye contact, give that tasteful head nod and carry on your way. Social intricacies aside, the premise seems simple, you see everyone who meets your preferences in the area, and are able to swipe away. However, underneath that simple clean interface, there appears to be other factors at play.

Over winter break, I decided to succumb to the Tinder craze. I downloaded the app, sloppily constructed my profile, and started swiping away. At first, I felt shallow, but quickly moved past that feeling as I got my first match. After a week or so of “normal” usage, I began to grow curious about how the app worked; I figured the app was showing me people who met my age and distance preferences. Some searching online, however, showed that this may not be the case. People were speculating about an internal ranking system, and the CEO of Tinder in an interview with Fast Company confirmed there is in fact an internal ranking system (https://poly.rpi.edu/s/iyqdh). Similar to the Elo score of chess players, your Tinder ranking determines how “desirable” your profile is, according to several factors, including the number of people who like your profile, the number of your right swipes that become matches, and some have even speculated, the amount you interact with your matches. The CEO mentioned the algorithm took months to develop, so it is not a simple to analyze function.

This brings a completely different question into play, one that I soon became obsessed with learning the answer to. Could you optimize Tinder? Could you create the so-called “perfect profile” to get the most matches? Knowing Tinder has this ranking algorithm turned the whole thing into a type of game for me—get better pictures, review them online, ask my friends about them, perfect my bio, and think of witty pickup lines. I even created a second identical account to see how swiping affected my perceived ranking. I began interacting with everyone, which not only allowed me to meet many new people, but also to boost that ever so important Elo score, and test out a whole slew of new pickup lines.

After a month or so of optimizing my profile, a question came to mind; with these algorithms controlling who sees who, is it fair to people involved? Is the algorithm helpful to the users, or is it simply a good business decision by Tinder? (More matches means more happy users). This algorithm, implemented after Nathan Dorer got his 1500 matches, as in a past editorial notebook of his, plays a hand in most Tinder interactions. With this in mind, I decided to stop my optimization obsession, and actually got to know some new people, talking to my algorithmically chosen best matches, and maybe meeting some new people “IRL.”

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