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Dating Apps and Nash Equilibrium


This article compares dating apps of India (Tinder and Tinder-like apps) and the West (such as Coffee meets Bagel and Bumble). The ratio of men to women on American dating apps is 6 to 4 and, even more than the skewed ratio, the activity of men on such apps being double that of women’s has overwhelming implications. This means more men proposition women through a “swipe right” because it is easy enough to do so. On Tinder, people have nothing to lose – no type of investment (monetary, time, emotional, or otherwise) goes into it. Because you cannot predict the answer of the other party, there is no need to be selective in your swipes.

This article relates to class concepts because in a Nash equilibrium every person engages in their best response to the other person’s predicted strategy. However, this pair of strategies ends up being worse for the group. Another example of the prisoner’s dilemma related to Nash equilibrium is what the author of this article calls “The Marriage Supermarket.” In this hypothetical market, $100 is given to a man and a woman to split equally (50-50) if they pair up. However, if the sex ratio becomes unequal (like it is on dating apps, as described above), the women who are left unpaired will try harder to become paired by offering a more unequal split of the money. However, the other woman who is then left unpaired will offer a more unequal split, getting the women into a bidding war that is essentially is “race to the bottom.” Eventually, the women’s share is very little. When applying this Marriage Supermarket to dating apps, instead of being money, the shared resource is the attention of women who use the app. It is for this reason that men’s “swipe right” activity is drastically higher on dating apps than women’s is due to individual incentives, eventually leading to a mutually bad situation. This article, thus, argues that dating apps would benefit from selectivity on systematic level. In the West, some apps already have improved upon Tinder, filtering results or adding a twist to the product in order to avoid the results of this phenomenon.


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September 2018