A couple weeks ago after my College Educated White Women post, the AVI sent along an Atlantic article about how everyone on dating apps is trying to date almost exactly 25% out of their league.
The bigger more attention grabbing headline from this study though, was the finding that women’s desirability peaked at age 18, whereas men’s peaked at age 50. They included this chart:
Since I always get hung up on how these things are calculated and what they’re really telling us, I decided to take a look at the paper and the supplementary materials. Here’s what I found:
- Desire = PageRank When looking at a study like this, one of the first things I always want to know is how they defined their terms. Here, the authors decided that using a model where desirability = the number of messages received would be too simplistic, so they decided to use the PageRank equation. Yes, from Google. This equation is useful because it doesn’t just measure overall number of messages received, but how desirable the people who got in touch with you were. So ten messages from desirable people were worth more than 100 from less desirable people…sort of like one link from a famous blogger is worth more than ten links from lesser known bloggers. This choice made a lot of sense as “desire” is not just about how many people want something, but also how hard it is to get. However, choosing this definition does have some interesting consequences, which I’ll get to in a minute.
- The pool was not randomly selected, and the most desirable people were the outliers When the AVI initially sent me this article, one of his first comments was that generalizing from a sample of dating website users was probably not a great idea. After looking at the sample, he was completely right. Not only are these dating website users, but they were exclusively dating website users in large cities. There were other interesting differences….like check out the demographics table: As a reminder, only about a third of US adults have a college degree. Those numbers for NYC are really unusual. You’ll also note that the average age of a user tended to be just over 30. So where did our highly desirable 18 year old women and 50 year old men fall? On the long tails: Yes, I drew pink and blue arrows to show where the most desirable men and women fell. Sorry about that. Anyway, as you can see, those who showed up as the most desirable were not the best represented. This makes a certain amount of sense….18 year olds don’t join dating sites as often because they are frequently still in high school and have lots of access to people their own age. 50 year old tend to be married, partnered, or otherwise not looking. This is important because it introduces the idea that those not in the peak age range for use (23-33 from what I can tell) may have some survivor bias going on. In other words, if they log on and are successful, they stay on the site. If they aren’t, they leave. From what I can tell in my friend group, a 30 year old will stick it out on dating sites until they find someone, because that’s simply what everyone does. Other age groups may have different strategies. Since all the data came from one month (January 2014) it would not capture people who came and went quickly.
- Desirable men and women probably don’t have the same experience One of the more interesting discussions in the “network analysis” section of the paper, was when the authors mentioned that they had to include two different measures of interest in order to cover both genders. Because men send 80% of the first messages, they realized that assessing “interest” only by first messages would basically mean they only knew who men were interested in. Given this, they decided to also include replies as markers of interest. Thus, while the same equation was applied to both genders, one suspects this plays out differently. Desirable women are likely those who get many messages from men, and desirable men are likely those who get a lot of replies from women. For example, the study authors note that the most popular person they found in their data was a 30 year old woman in NYC who received over 1500 messages (!) in the one month they studied. They don’t list how the most popular male did, but one has to imagine it’s an order of magnitude less than that woman. It’s simply much harder to compose messages than it is to receive them, and with reply rates hovering at 15-20% one imagines that even extremely popular men may only be hearing back from around 100 women a month. In other words, the experiences of the genders are hard to compare, even when you use the same grading criteria.
- Decreasing your messages out would increase your page rank Okay, back to the PageRank system. Ever since Google first released their PageRank algorithm, people have been trying to optimize their sites for it. While Google has definitely tweaked their algorithm since releasing it, this study used the original version, which used the number of links your site makes as a divisor. In other words, the less you link to other sites, the higher your own rank. An example: suppose an 18 year old woman and a 30 year old woman get 100 messages from the exact same group of men. The 18 year old kinda freaks out and only replies to 1 or 2. The 30 year old woman seriously wants to find someone and replies to 20. Per PageRank, the 18 year old is rated more highly than the 30 year old. Now take a 30 year old man and a 50 year old man. The 30 year old man is all in on his dating app game, and messages 100 women, receiving 20 replies. The 50 year old man isn’t quite as sure and carefully selects 10 messages to women he thinks he has a chance with, getting 3 replies. If those replies came from “higher ranking” women than the 20 the other guy got, the 50 year old is now more “highly desirable”. In other words, users who are highly engaged with the dating site and taking chances will not do as well ranking-wise. Being choosy about who you reply to/message helps.
- Some of this may be up front decision making rather than personal One of the weirder downsides to online dating is the ability to set hard stops on certain characteristics of others. While in pre-computer days you would generally find out someone’s attractiveness first, now you can ask the site only to show you matches that are taller than 6’/older than 25/younger than 40, and the algorithm will do exactly what you say. This almost certainly impacts messaging behavior, and it turns out men and women approach ages limits really differently. OKCupid pulled their data on this, and here’s what they found: So our median male keeps 18 year old women in his age range for 5 years of his life (18-23), while our median female will only date 18 year old men for 2 years (18-20). It appears once women get out of college and hop on a dating site they pretty much immediately want to drop college aged men. On the other end, 48 year old men have a preferred age range nearly double the size of the age range 48 year old women set. Men raise their floor as they age, just not nearly as quickly as women do. Both genders appear to raise their ceiling at similar rates, though women always keep theirs a little higher. Thus, younger women will always be receiving messages from a much larger pool of men than older women, particularly since participation in dating sites drops off precipitously with age. A 30 year old woman (the average age) has men 26-46 letting her through their filter, whereas a 30 year old man has women 26-35 letting him through theirs.
Well there you have it, my deep dive in to desirability and PageRank as applied to dating! For any of you single folks out there, it’s a good time to remind you that just like Google results, online dating can actually be hacked to optimize your results, and that the whole thing is not a terribly rational market. Good luck out there!
3 thoughts on “5 Things About Peak Desirability”
Fascinating Stuff. I have already started to listen to that TED talk. But my first fascination was wanting to hear about that 30 y/o woman from NYC who got all the attention. What was on her profile that worked so well? I want to know her story, how she got there and what happened after. Someone needs to write a script about this.
I know! I actually looked up the TED talk because I actually wondered if it was the same person, because I think she mentions that her hacking worked so well she became the most popular user for a brief period. She released her talk earlier than the study, though of course this woman could have been using similar tactics.
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