While most leisure activities were throttled by the Covid lockdown, others thrived – just ask any of your friends who did Yoga With Adrienne. Another unlikely winner? Dating apps. Tinder and Bumble usage in New Zealand alone rose by over 20%, with Tinder registering 3 billion swipes globally on 28 March alone.
However, the pandemic only accelerated a trend that was already in full force: finding love via apps. “Met online” is now the most common way that people report finding their significant other, streets ahead of boring old classics like “met in church” or “met in the neighbourhood”. While there are a range of massively popular dating apps, including Bumble and Grindr, Tinder continues to be the most popular platform by a significant margin. That gives the company a pretty crazy level of influence over how young people date and, yes, who they match with.
Understandably, Tinder has furiously back-tracked from the disastrous PR of dividing its users into looks-based tiers
Make no mistake: nothing about the Tinder algorithm is random. When you open the app to get swiping, you might think that the profiles you are seeing are just a random bunch of people that fit your age/gender preferences and live relatively close. Think again. Tinder wants to match as many couples as possible and designs its algorithm to put certain profiles in front of you. Of course, you’re free to swipe right to your heart’s delight and ignore the people Tinder recommends, but the algorithm penalises you for swiping left too much. So how does Tinder decide whose profiles to show you?
A few years ago, Tinder made the mistake of showing a journalist for Fast Company what was actually under the algorithm’s hood – and it wasn’t pretty. As that journalist details, the Tinder algorithm allocates every user a personalised “desirability” score, to represent how much of a catch any particular person is. Users are then sorted into tiers based on their desirability score, and that was, in essence, the algorithm: you get presented with people approximately your level of attractiveness when you swipe.
(As an aside, the whole article is worth reading as a slow-moving train wreck – Tinder CEO Sean Rad boasts about his own desirability score as “above average” before defending the scores as not solely determined by profile pictures. The journalist is informed that his personal score is “on the upper end of average” in a hall-of-fame calibre neg, and the CEO helpfully notes that they intentionally called the score “desirability”, not “attractiveness”. Not all heroes wear capes, dear readers).
It seems like the only real change to Tinder’s algorithm is to incorporate more machine learning – so the app tries to learn what you like based on the profiles you swipe right on, and show you more of those profiles
How does Tinder work out how desirable (read: hot) you are? Using a so-called “ELO” system, inspired by how chess players are ranked (yes, really!). It’s pretty simple: if people swipe right on you, your desirability score goes up, and it goes down if people instead give your profile a pass. If someone with a high score swipes right on you, that increases your score more than someone with lower “desirability”. This is problematic in all kinds of ways, not least of which that Tinder is shamelessly focused on physical appearance. Bios are tiny and the app instead encourages you to upload multiple high-quality photos. You can’t blame that Fast Company journalist for wondering whether his desirability score was an objective measure of how good looking he was.
However, while in this blog post it calls its ELO-rating system “old news”, the company concedes it still uses the same basic mechanic of showing you different sets of profiles depending on how many swipes you’re getting. Again, however, the company will only show you people it thinks are reasonably likely to swipe on you.