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Matching and sorting in online dating

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The dynamics of dating have been discussed and dissected extensively, but in this post we can hopefully gain some new insights into it by viewing it as a networked market. What makes this market quite interesting is that there is no explicit currency, price, or transfer mechanism. Hence, an agent may have high currency or desirability for one person and low desirability for another, and the preferences may not necessarily be monotonically related to their attributes. This makes matching in the market quite interesting as individual preferences are likely to be heterogenous. Efficient matching in this market thus relies on the existence of pairs of mutually desirable agents in a setting where all preferences are heterogenously distributed.
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Matching and Sorting in Online Dating

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Matching and Sorting in Online Dating

Using data on user attributes and interactions from an online dating site, we estimate mate preferences, and use the Gale-Shapley algorithm to predict stable matches. The predicted matches are similar to the actual matches achieved by the dating site, and the actual matches are approximately efficient. Outof-sample predictions of offline matches, i. Thus, mate preferences, without resort to search frictions, can generate sorting in marriages.
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Skip to search form Skip to main content. The predicted matches are similar to the actual matches achieved by the dating site, and the actual matches are approximately efficient. Outof-sample predictions of offline matches, i.
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