  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 the distribution of likes among different users
is not trivial. In this paper we show how likes are distributed across users,
based on different decision-making strategies and on different app settings. We
apply theoretical methods originally developed in stochastic and coagulation
processes to the investigation into the dynamics of dating app networks. More
specifically, we show that whenever a dating app differentially displays
different users with respect to their popularity in different models, users are
split into two categories: a first category including users who have received
most likes and a second category, referred to as a condensate, which in the
long-term will be reduced to a small fraction of likes or to no likes at all.
Finally, we explore different models based on a rating system of the users,
known as Elo. These models will turn out to exhibit behaviour typical of
gelating systems and non-trivial distribution of Elo rating.
