Tinder study confirms that 80/20 rules applies to sexual attraction

Abstract

This study was conducted to quantify the Tinder socio-economic prospects for males based on the percentage of females that will “like” them. Female Tinder usage data was collected and statistically analyzed to determine the inequality in the Tinder economy. It was determined that the bottom 80% of men (in terms of attractiveness) are competing for the bottom 22% of women and the top 78% of women are competing for the top 20% of men. The Gini coefficient for the Tinder economy based on “like” percentages was calculated to be 0.58. This means that the Tinder economy has more inequality than 95.1% of all the world’s national economies. In addition, it was determined that a man of average attractiveness would be “liked” by approximately 0.87% (1 in 115) of women on Tinder. Also, a formula was derived to estimate a man’s attractiveness level based on the percentage of “likes” he receives on Tinder:

attractiveness%=16.8*ln(like%)+52.3

The Data

As I stated previously the average female “likes” 12% of men on Tinder. This doesn't mean though that most males will get “liked” back by 12% of all the women they “like” on Tinder. This would only be the case if “likes” were equally distributed. In reality, the bottom 80% of men are fighting over the bottom 22% of women and the top 78% of women are fighting over the top 20% of men. We can see this trend in Figure 1. The area in blue represents the situations where women are more likely to “like” the men. The area in pink represents the situations where men are more likely to “like” women. The curve doesn’t go down linearly, but instead drops quickly after the top 20% of men. Comparing the blue area and the pink area we can see that for a random female/male Tinder interaction the male is likely to “like” the female 6.2 times more often than the female “likes” the male.

We can also see that the wealth distribution for males in the Tinder economy is quite large. Most females only “like” the most attractive guys. So how can we compare the Tinder economy to other economies? Economists use two main metrics to compare the wealth distribution of economies: The Lorenz curve and the Gini coefficient.

The Lorenz curve (Wikipedia link) is a graph showing the proportion of overall income or wealth assumed by the bottom x% of the people. If the wealth was equally distributed the graph would show a 45 degree line. The amount the curve bends below the 45 degree line shows the extent of wealth inequality. Figure 2 shows the Lorenz curve for the Tinder economy compared to the curve for the U.S. income distribution from a few years ago.

The Lorenz curve for the Tinder economy is lower than the curve for the US economy. This means that the inequality in Tinder wealth distribution is larger than the inequality of income in the US economy. One way economists quantify this difference is by comparing the Gini coefficient for different economies.

Another study, reported in Business Insider, found a pattern in messaging on dating apps that is consistent with these findings. Yet another study, run by OkCupid on their huge datasets, found that women rate 80 percent of men as “worse-looking than medium,” and that this 80 percent “below-average” block received replies to messages only about 30 percent of the time or less. By contrast, men rate women as worse-looking than medium only about 50 percent of the time, and this 50 percent below-average block received message replies closer to 40 percent of the time or higher.

Conclusion:

If these findings are to be believed, the great majority of women are only willing to communicate romantically with a small minority of men while most men are willing to communicate romantically with most women. The degree of inequality in “likes” and “matches” credibly measures the degree of inequality in attractiveness, and necessarily implies at least that degree of inequality in romantic experiences. It seems hard to avoid a basic conclusion: that the majority of women find the majority of men unattractive and not worth engaging with romantically, while the reverse is not true. Stated in another way, it seems that men collectively create a “dating economy” for women with relatively low inequality, while women collectively create a “dating economy” for men with very high inequality.

There are no villains in this story. Nobody can or should be blamed for his or her honest preferences, and if women collectively believe that most men are unattractive, what grounds does anyone, male or female, have to argue with them? We may pity the large majority of men who are regarded as unattractive and who have few or no romantic experiences while a small percentage of attractive men have many. Just as much, consider that we live in a monogamous culture, and so the 20 percent of men who are regarded as attractive can only be in committed relationships with at most 20 percent of women. We may just as well pity the rest of the women, who are destined to be in committed relationships, if they pursue a relationship at all, with someone who they regard as unattractive. The only villain in this story is nature, which has molded our preferences so that this tragic mismatch of attraction and availability occurs.