How you are being categorized by Tinder algorithm

Emily doesn’t swipe anymore. As 57 million people around the world, she was using Tinder. The 21 years old student is now in a relationship. But anyway she may be more reluctant to use the American dating app. More than ever.

‘At best a client, at worst, a product’

Indeed, it has recently been reported by the French journalist Judith Duportail that Tinder was rating people to make accurate suggestions. In her 2019 book L’amour sous algorithme (The Love algorithm), she unveils the existence of the Elo Score, that is to say a desirability rate. Judith Duportail received 800 pages of personal data as stated by the European law on data protection. She had everything : conversations, places geolocated, likes. Everything but her Elo Score.

‘At best a client ; at worst, a product’ Duportail claims, as she shows that the app heighten inequalities within relationships, encouraging men to date younger women, less wealthy and with a poorer education background.

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Emily told us that she had been using the app for ‘a fair amount of time’. She wasn’t looking for anything serious at the time. She ‘thought it’d be a good laugh, a good way to meet new people’. Yet, she quickly noticed that the algorithm was shaping her experience.

I did find it quite addictive and I also noticed that it would stop showing me certain kind of people after a while. And it did feel like it filtered out, based on things like education level, potentially race, or the kind of jobs people had.

Even though the terms and conditions are public, there is allegedly no way for users to find their rate nor to know the way it is calculated. The underlying coding programs are not revealed by Tinder but would apparently be based on the success of our profile picture, the number of complicated words used in the chat.

The app even goes further : people do not have the same clout on our value, as it depends on their own rate. In 2019, the Vox reported that ‘the app used an Elo rating system, which is the same method used to calculate the skill levels of chess players: You rose in the ranks based on how many people swiped right on (“liked”) you, but that was weighted based on who the swiper was. The more right swipes that person had, the more their right swipe on you meant for your score’.

Tinder stated on their blog that the Elo Score was old news, an ‘outdated measure’ and now, the app was relying on the activity of its users. 

According to tinder’s website, ‘Tinder is more than a dating app. It’s a cultural movement.’ 

In a sense, this is not only marketing, this is partly true. Tinder is now renowned worldwide. 9% of French couples who started their relationship between 2005 and 2013 met online according to the National Institute of Demographic Studies. In the UK, based on an Infogram study, this number reached 20% in 2013 and 70% for the same-sex couples according to sociologists Reuben Thomas and Michael Rosenfeld. 

Birds of a feather flock together

Sociologists haven’t been waiting for social media to identify the phenomenon of endogamy (or in-marriage) : we tend to date people from the same social class. We share similar activities and meet them within familiar groups : colleagues, friends, friends of friends. Thus, digital categorizing is pushing further existing dynamics.

When I swiped right, Emily says, it would show me more of those people. That is obviously kind of reinforcing social stratification, I guess, and the fact that people tend to end up with the ones that are similar to them.

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Camille, a 21 years old bisexual user of the app, also noticed she was shown similar profiles. She told us that it appeared ‘rather obvious when you use the app’. Yet, Camille thinks it helps to find someone you are likely to meet in real life.

It seems as a good way to select the people to interact with. It seems rather innocent. It’s not something you give a lot of thoughts about.

Indeed, Tinder’s algorithm aims at finding the same interests, equivalent wages (if you tell your job in your description, the average income can be found). But key words can be identified without being understood. Surprisingly enough, Tinder doesn’t get irony or expressions, hence awkward date experiences.

The biases of machine-learning systems 

This might be a matter of time. As Diggit Magazine recently reported, algorithms are machine-learning systems, fed by societal practices. This can be for the best… And the worse. That is to say that this love conditioning has its biases as the app can be supplied with racist or sexist contents. 

Moreover, Aude Bernheim unveiled in her AI study L’intelligence artificielle, pas sans elles ! that 88% of algorithms were made by men.

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It might account for the unbalance within Tinder’s users. Only 38% of Tinder users are female against 62% of males. The experience as female queer user also raises questions as Camille’s story proves.

About women, I noticed that the app had lots of problems identifying the kind of girls I would like to date. I do believe that for queer people, especially women, it is actually harder to interact on the app. There are so many couples looking for a third person. So the algorithm works when you want an heterosexual relationship but for queer people… It does not work as well as it should. It is sadly predictable and that’s probably why I stopped using Tinder.

The app is well aware of these situations and tries to look inclusive on its website “Swipe life” made out of articles on ‘dating tips’ such as ‘How to Talk to Your Partner About Non-monogamy’ or ‘What You Should Know When Dating Someone With Bipolar Disorder’. Yet, the lack of transparency on their algorithm is still widely criticized. 

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They also seem to put the emphasis on who insignificant dating has become. They report on their website that ‘70% of these college students have never met up with their matches…and 45% say they use Tinder mostly for confidence boosting procrastination’ Dating is no longer a big deal. But it is a big business as the app now has 800 million euros of annual turnover.

If the categorization seems harder to understand due to the end of the Elo Score, both analysts and users claim the profiling hasn’t come to an end yet.

Melanie Lefkowitz wrote that ‘Although partner preferences are extremely personal, it is argued that culture shapes our preferences, and dating apps influence our decisions.’ And Emily couldn’t agree more as she experienced it herself.

On the one hand, it really opens up your circle because there’s suddenly all those people you would never have bumped into in your life but you can message, and meet up with. On the other hand, the algorithm kind of dictates who you’re able to see as being out there. It’s actually quite limiting.