For the Love of Economics
From casual dating to serious relationships, technology has had a profound impact on dating. Further, if we were to delve deeper, we would be amused to see how economics and game theory infiltrate the realm of online dating.
A man, say Henry, wants to get into the online dating “market” and is confused among the deluge of dating apps that exist today. Choosing an app is the very first and, perhaps, one of the most difficult parts of the online dating process. However, economics might help him out! On one side of the spectrum are apps like Tinder and Match.com, offering a large user base and a very high number of potential matches. This kind of apps constitute what is known as a “thick market”. While a thick market might offer more options, there is a possibility that one might encounter many casual profiles. On the other side, there are apps like Veggly, which targets the vegan singles market, and Datefit, a dating app for fitness freaks. These platforms constitute a “thin market”, which has a small, specialized group of people. While a thin market is best suited for those who are looking for “specific” traits in their partners, this specificity contracts the pool of potential matches. Depending on the kind of people Henry wants to date, he can choose the most suitable app.
Once Henry chooses an app and creates a profile, he needs to figure out a strategy on how to find proper matches for himself. Chalking out a prudent strategy becomes even more important because he has limited time in which he has to go through several profiles and arrive at the right one. He will keep reviewing more profiles only if he thinks that the marginal utility from the chance that the woman of the next profile can become his life partner surpasses the marginal utility from spending his time in some other pursuit. In other words, he has to stop searching at some point, maybe temporarily.
Henry might have to decide when to stop searching at almost every stage of the online dating process. First, there’s the question of whether he should look at one more profile or not. Next comes the decision of whether to go on subsequent dates with a woman he has met once, or to search for an alternative potential partner. Then, if he has been seeing someone for a while, he must decide whether to commit to seeing only that person, maybe “settle” with her, and ultimately marry—or whether to return to the market and try his luck again. Finally, even when he is in a long-term relationship, he has to continually decide whether the relationship he currently has is better than the alternative of breaking it off and trying for a better one. Hence, throughout the course of online dating, Henry might be implicitly facing tradeoffs between what he has and what he could have found otherwise.
Once Henry chooses an app, it will ask him for his preferences—for instance, whether he is looking for a serious relationship or just a dalliance—and to furnish demographics like age, level of education, weight, height and location. Thanks to positive assortative mating, people mostly tend to end up with those who are similar to them, both in terms of objective characteristics like education and geographic vicinity, as well as subjective measures like appearance and personality attributes. The basic idea behind positive assortative mating is that people sort into partnerships or groups in a manner that is non-random and ordered.
Considering that Henry employs positive assortative mating to filter profiles, there is still a possibility that he might have hundreds of profiles to choose from. How can he narrow down his search even further? This is where Game Theory can come to his rescue. While using the app, he should try and identify the dominant strategy for each player in the market. In the game-theory parlance, the dominant strategy is the best strategy that Henry can employ as a response to all the possible strategies that the other players might use. On most dating apps the available strategies are: swipe right and try to match, or swipe left in order to reject. If his aim is to maximize the matches, he should always swipe right as he can match with all the women who have swiped right on his profile. However, the downside is that many women might play the dominant strategy of swiping right on every man’s profile and if Henry responds by swiping right on all of their profiles, it would again leave him with many matches and probably, of low quality. For instance, Tinder’s algorithm disincentivizes the tendency of swiping right a lot by restricting people to 100 right swipes per day. This is done to make sure that an individual is genuinely looking at the profiles and not just randomly spamming them so that the experience of using the app feels useful and real . Further, if the algorithm finds a person to be too “swipe-happy”, it might show his profile to fewer users, resulting in a lesser number of matches for him. Therefore, if Henry uses an app where a significant portion of women swipe right on every profile, the best way out would be to swipe left unless he is “seriously” interested in a particular woman.
A very interesting feature of Tinder’s algorithm is that it makes use of two primary factors-location and age preferences- to serve profiles to users. Assuming that younger people would be more venturesome and willing to meet different kinds of people, they might consider swiping right on the profiles most of the time, if not always. However, assuming that older people are more aware and conscious of their preferences in a partner, they might consider swiping right only if they are genuinely interested in a profile. This becomes especially useful for them if they do not want to waste a lot of time on the search and desire for a long-term relationship.
No one is immune to the temptation of exaggerating a bit. But the issue arises when the exaggeration goes to the extent of lying about oneself. Since nothing on dating apps is verified, “cheap talk” is ubiquitous. Most people lie about their age, weight, height etc. Cheap talk is the information which is costless for the sender to provide and does not directly affect the payoffs of the entire process. So, how could Henry differentiate cheap talk from authenticity?Assuming that Henry wants to find a long-term partner, he can resort to cooperative game theory strategies. Cooperative game theory models are used when the interests of the involved parties are perfectly aligned. For a cooperative model of online dating to work properly, nobody would have anything to hide, and all potential daters would reveal as much as they possibly can. This means that the women who are attracted to Henry would be exactly the same women who are attracted to his completely honest and thoroughly informative online profile. Nevertheless, however much Henry would want to be loved for the person that he genuinely is, things might turn out to be much more complex. For instance, Henry can find a woman very attractive and even she reciprocates. But, at the same time, she finds his favorite holiday destination to be boring or his favorite dish insipid. In such a case, Henry can decide to hide these trivial details. He can reason out that even if the woman eventually finds out these things once they are into a serious relationship, she might avoid or accept such trivia as a part of the whole package. That’s cooperative game theory. Their interests are aligned, and Henry simply removes some minor obstacles. Henry should be able to differentiate cheap talk from signaling. A signal is a message that is costly for the sender, and so, it most certainly is credible. So, whenever he is looking out for profiles, he should remain watchful of costly signals and skeptical of cheap talk.
Far be it from economists to offer dating advice, but for all you know, if you do end up finding a likewise Game-Theory-minded partner, you’d know better than to engage in a Battle of the Sexes.
SY BSc Div-2 (20-23)