Towards a statistical physics of dating apps

Abstract

Abstract Over the last ten years, a sharp rise in the number of dating apps has broadened the spectrum of how one can get in contact with new acquaintances. A common feature of such apps is a swipe, enabling a user to decide whether to like or dislike another user. As is the case in real life, a user may be more or less popular, which implies that the distribution of likes among different users is broad. In this paper, we show how likes are distributed across users, based on different decision-making strategies, app settings and their feedback. We apply theoretical methods originally developed in non-equilibrium statistical physics to investigate the dynamics of dating app networks. More specifically, we show that whenever a dating app differentially displays users with respect to their popularity, users are split into two categories: a first category including users who have received the most likes and a second category, referred to as a condensate, which in long-term will be reduced to a small fraction of likes or to no likes at all. Finally, we explore realist models based on a rating system of the users, known as Elo. These models will turn out to exhibit behaviour typical of gelating systems, characterized by a bimodal distribution of likes among the users with broad tails. Altogether, we provide a minimal theoretical framework to infer statistical observables in social networks governed by coupled internal states.