Bad dating profiles tumblr. Darwin Dating Awards.



Bad dating profiles tumblr

Bad dating profiles tumblr

Female Tinder usage data was collected and statistically analyzed to determine the inequality in the Tinder economy. The Gini coefficient for the Tinder economy was calculated to be 0. This means that the Tinder economy has more inequality than I wanted to understand this trend in more quantitative terms also, I like pretty graphs. To do this, I decided to treat Tinder as an economy and study it as an economist would.

The wealth of an economy is quantified in terms its currency. In most of the world the currency is money in other places it is still goats. Wealth in Tinder is not distributed equally. An unequal wealth distribution is to be expected, but there is a more interesting question: What is the degree of this unequal wealth distribution and how does this inequality compare to other economies? To answer that question we are first going to need some data and a nerd to analyze it.

I asked them each several questions about their Tinder usage while they thought they were talking to an attractive male who was interested in them. Lying in this way is ethically questionable at best , but I had no other way to get the required data. Caveats skip this section if you just want to see the results At this point I would be remiss to not mention a few caveats about these data. First, the sample size is small only 27 females were interviewed.

Second, all data is self reported. This self reporting bias will definitely introduce error into the analysis, but there is evidence to suggest the data I collected have some validity. I have to assume that in general females find the same men attractive.

I think this is the biggest flaw in this analysis, but currently there is no other way to analyze the data. There are also two reasons to believe that useful trends can be determined from these data even with this flaw. First, in my previous post we saw that attractive men did equally as well across all female age groups, independent of the age of the male, so to some extent all women have similar tastes in terms of physical attractiveness.

Second, most women can agree if a guy is really attractive or really unattractive. Women are more likely to disagree on the attractiveness of men in the middle of the economy. We can see this trend in Figure 1. We can also see that the wealth distribution for males in the Tinder economy is quite large.

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.

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. 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.

The Gini coefficient Wikipedia link is a number between 0 and 1, where 0 corresponds with perfect equality where everyone has the same income damn commies and 1 corresponds with perfect inequality where one person has all the income and everyone else has zero income let them eat cake.

The Tinder Gini coefficient is even higher at 0. This may not seem like a big difference but it is actually huge. Figure 3 compares the income Gini coefficient distribution for nations and adds the Tinder economy to the list. The Tinder economy has a higher Gini coefficient than This graph is shown as Figure 4. Note that the y-axis is in log scale and the curve is fairly linear. This means the curve has a high correlation to an exponential fit.

So attractive guys can do pretty well using Tinder congratulations. Unfortunately, this percentage decreases rapidly as you go down the attractiveness scale. You can be of above average attractiveness and still only get liked by a few percent of women on Tinder. You would probably be better off just going to a bar or joining some coed recreational sports team.

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Bad dating profiles tumblr

Female Tinder usage data was collected and statistically analyzed to determine the inequality in the Tinder economy. The Gini coefficient for the Tinder economy was calculated to be 0. This means that the Tinder economy has more inequality than I wanted to understand this trend in more quantitative terms also, I like pretty graphs. To do this, I decided to treat Tinder as an economy and study it as an economist would. The wealth of an economy is quantified in terms its currency.

In most of the world the currency is money in other places it is still goats. Wealth in Tinder is not distributed equally. An unequal wealth distribution is to be expected, but there is a more interesting question: What is the degree of this unequal wealth distribution and how does this inequality compare to other economies?

To answer that question we are first going to need some data and a nerd to analyze it. I asked them each several questions about their Tinder usage while they thought they were talking to an attractive male who was interested in them.

Lying in this way is ethically questionable at best , but I had no other way to get the required data. Caveats skip this section if you just want to see the results At this point I would be remiss to not mention a few caveats about these data.

First, the sample size is small only 27 females were interviewed. Second, all data is self reported. This self reporting bias will definitely introduce error into the analysis, but there is evidence to suggest the data I collected have some validity.

I have to assume that in general females find the same men attractive. I think this is the biggest flaw in this analysis, but currently there is no other way to analyze the data. There are also two reasons to believe that useful trends can be determined from these data even with this flaw. First, in my previous post we saw that attractive men did equally as well across all female age groups, independent of the age of the male, so to some extent all women have similar tastes in terms of physical attractiveness.

Second, most women can agree if a guy is really attractive or really unattractive. Women are more likely to disagree on the attractiveness of men in the middle of the economy. We can see this trend in Figure 1. We can also see that the wealth distribution for males in the Tinder economy is quite large. 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. 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. 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. The Gini coefficient Wikipedia link is a number between 0 and 1, where 0 corresponds with perfect equality where everyone has the same income damn commies and 1 corresponds with perfect inequality where one person has all the income and everyone else has zero income let them eat cake.

The Tinder Gini coefficient is even higher at 0. This may not seem like a big difference but it is actually huge. Figure 3 compares the income Gini coefficient distribution for nations and adds the Tinder economy to the list. The Tinder economy has a higher Gini coefficient than This graph is shown as Figure 4. Note that the y-axis is in log scale and the curve is fairly linear.

This means the curve has a high correlation to an exponential fit. So attractive guys can do pretty well using Tinder congratulations. Unfortunately, this percentage decreases rapidly as you go down the attractiveness scale. You can be of above average attractiveness and still only get liked by a few percent of women on Tinder. You would probably be better off just going to a bar or joining some coed recreational sports team.

Bad dating profiles tumblr

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