Alexander Profile picture
Jan 4 26 tweets 7 min read
Did the invention of Tinder result in an increase of casual sexual activity?

Evidence from 1.3 million college students between 2012 and 2016. 🧵
Online dating is now one of the top ways people form relationships. About 39% of relationships began on apps as of 2019.

However, rather than a relationship formation tool we often associate apps with casual sexual activity in popular culture.
Researchers examined a very large sample (1.3M) of college students between 2012 and 2016 using the National College Health Assessment (NCHA) survey to estimate a relationship between Tinder use and sexual activity.
Greek-affiliated fraternity/sorority members saw a small increase in total and monthly sexual partners over the last month, by about 6.3% and 3.4%.

Or, about .11 and .07 standard deviations.
Greek fraternity/sorority students were also more likely to contact an STD or unplanned pregnancy following the Tinder rollout - but only by 0.2%.
This effect was concentrated in the top 25% of men: 4.3% of the increase in sexual partners (of the 6.3% total).
In other words, the top 25% of men saw an increase in sexual partners of 4.3%.

The bottom 75% saw an increase in sexual partners of 2%.
Tinder may have helped the top 25% of men twice as much!

At the same time, it also helped them remarkably little.

A 4.3% increase in sexual partners is almost nothing.
This is contrary to the belief that Tinder has had a large role in facilitating casual sex.

It is more consistent with past research on dating apps that has found people primarily do not use them for casual sex:

mdpi.com/1660-4601/17/1…
It's also contrary to the popular narrative that Tinder has funneled easy access to casual sex into the grasp of the top tier of men.

Or, the belief that the top 20% is having 80% of the sex.
The average number of yearly sexual partners for people in the top 25% was 2.

The median number was 1.

For 30 days, 1 was the value for both the median and the top 25%.
The effect was similarly small for non-Greek students (not in a fraternity or sorority).
I also see people say that Tinder use has disrupted relationship formation.

That people are forgoing relationships for "situationships" and casual sex.

But we we don't see a decline in relationships associated with the advent of Tinder either:
This can also be seen in the nationally representative GSS data. Relationship rates have not declined:

datepsychology.com/how-have-relat…
The effect of Tinder on sexual outcomes for women was also the same (or smaller but not statistically significant) as it was for men.

Contrary to some claims that Tinder has resulted in more sex for women, but less sex for men.
A few statistical comments beyond this point:

When we correlate changes in behavior following an event, it is sometimes described as a "quasi-causal" methodology.

The idea being that you can compare before/after an event to see if the event had an effect.
Ultimately it is still a correlation however, so be cautious in interpreting "causal" this way.

Without assignment to groups it strictly can't be known if your variable had a casual effect.
A word can be said about statistical significance and effects sizes as well:

When you have a large sample, almost any change at all will be statistically significant.

Even if the change is very small, not "clinically/practically" significant, or not meaningful.
Here we see what is effectively less than one additional yearly sexual partner on average following the Tinder rollout - so a pretty good example of "statistically significant, but not meaningful."

You should always look at effect sizes.
You could also interpret this from seeing the size of the increase in standard deviations, which correspond to the Cohen's d effect size conventions: very small at .11 or .07

This is what it would look like:
What are the take home points for this?

Maybe two big ones:

1. There is surprisingly little difference in sexual activity between the top 25% of men and the top 50%.
2. The Tinder rollout was only very weakly associated with more sex.

Even among college students, who we tend to think of as highly sexually active - and even for the Greek frat/soror students we tend to think of as the most popular and sexually active!
Why could this be - certainly the most attractive men could have more sex?

People likely underestimate the general trend (especially for handsome men) of forming monogamous relationships.

Rather than pursuing high levels of promiscuity, more common is entering a relationship.
Indeed - we see a large majority of sex occurs in relationships with a committed partner in representative data:

datepsychology.com/how-many-sexua…
A common trajectory for handsome men on dating apps: they find a relationship easily, but are taken off of the sexual market as they enter into that relationship.

Thus, keeping absolute partner count lower than it might have been had they pursued a promiscuous strategy.

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More from @datepsych

Jan 5
Fascinating speed-dating study using fMRI.

What I like about this methodology is asking "how much would you like to date this person" rather than giving just a 1-7 Likert attractiveness rating.

This was done while participants were in the fMRI.

They would go on to meet.🧵 Image
There was no difference between actual pursuit rates - people actually picked to date once they met - between men and women.

A bit different from what we often see in attractiveness ratings, when men are rated lower by women. Image
Ratings of attractiveness and ratings of likability were both predictors of who was picked for a second date. Attractiveness was higher. Image
Read 19 tweets
Jan 5
What can rising STD rates tell us about promiscuity and sexual behavior? 🧵
Something I see discussed infrequently in the general promiscuity discourse online is STDs.

Which is highly surprising - given how higher rates of promiscuity are associated with a higher likelihood of contracting an STD.
Indeed, having more lifetime sexual partners is associated with higher risk of having contracted an STD.

The more partners, the higher the risk.

Giving us the so-called "promiscuous 10%" that are associated with disproportionate rates of transmission.

jech.bmj.com/content/58/11/… ImageImage
Read 25 tweets
Jan 3
Although these calculators make it seem as if it is difficult to find an adequate partner, this is not the case.

Mate choice is not random.

The probability of finding a mate in one of the below categories is not the same as the total prevalence in the general population. 🧵
For example, at face value you would consider these standards (man in fig 1, woman in fig 2 above) very reasonable.

And yet, the combined probability of the two together would be lower than 1% - if it were a random assortment from the general population.
The probability of finding a mate with X characteristic depends on the pool you are selecting a mate from.

It depends on the people you come into contact with each day.

This is part of what is called assortative mating.

sciencedirect.com/topics/biochem…
Read 14 tweets
Jan 2
Here are the results of a recent poll. I asked people to imagine 100 dating-age peers and tell me if at least half were attractive enough to date.

Most people don't find most people attractive.

So - how is it that most people are in relationships? 🧵
This is a result I expected. Most people don't find most people attractive.

Women are also more selective than men.
This raises a question - how is it that so many people are in relationships and married when we don't find most people physically attractive enough for a relationship?

Let's look at how this works out with something like facial attractiveness.
Read 18 tweets
Jan 1
Are the top 20% of men showered with attention and are "Chads" poaching average women on dating apps?

What the OKCupid data show. 🧵
This chart is often interpreted to show that men are "fair" with women on dating apps. However, these are just ratings. Image
Here are ratings against a distribution of actual messages - "revealed preferences" if you will.

These charts are kind of a mess. ImageImage
Read 25 tweets
Dec 30, 2022
Poll time:

Imagine you feed 100 people some nasty dog poo.

You ask them to rate the taste on a scale of 1-10.

Would you expect 68% of people to rate it between a 4-5 - approximating a normal distribution?

Or would the chart look more like the the second?
It is not a trick question btw.
I think we all learn about the central limit theorem and how we end up with normal distributions in samples.

But if a normal distribution exists or not depends on if the data is actually normally distributed.

Like in real life, in the population.
Read 9 tweets

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