  This paper deals with the estimation of population sizes for
respondent-driven sampling (RDS), a variant of link-tracing sampling that
leverages social networks over a number of waves to recruit individuals from
hidden populations. The RDS process is mostly controlled by individual
participants who might report on recruitment proposals, or nominations, that
they have received or given. By considering all nominations given or received
over a time period, one can create a capture-recapture dataset in which units
are individuals who have received at least one nomination and capture occasions
are either time intervals or recruitment waves, with the goal of estimating the
size $N$ of the hidden population. In this paper, we argue that the underlying
process that generated the RDS nomination data is that of a capture-recapture
experiment. We then proposed a methodology for the estimation of the population
size and investigated its performance against departures from classical
capture-recapture assumptions.
