Folk Theories and User Strategies on Dating Apps

The goal of this paper is to understand the experience of users with algorithmic filtering on dating apps by identifying folk theories and strategies that users employ to maximize their success. The research on dating apps so far has narrowly focused on what we call algorithmic pairing-an explicit pairing of two users together through a displayed compatibility score. However, algorithms behind more recent dating apps work in the background and it is not clear to the user if and how algorithmic filtering is mediating their interaction with other users. This study identifies user goals and behaviors specific to dating apps that use algorithmic filtering: while some users employ various strategies to boost their "attractiveness score" to match with as many people as possible, others attempt to teach the algorithm about their unique preferences if they believe that the filtering is not working in their favor. Our research adds to the growing literature on folk theory formation by introducing dating apps as a novel context for research. Since folk theories are developed with specific goals in mind, they reveal user concerns around algorithmic filtering. Our hope is that this paper starts a conversation on the practical and ethical question of algorithmic intervention on sexual and romantic preferences and behavior.