  Many dynamic networks coming from real-world contexts are link streams, i.e.
a finite collection of triplets $(u,v,t)$ where $u$ and $v$ are two nodes
having a link between them at time $t$. A very large number of studies on these
objects start by aggregating the data in disjoint time windows of length
$\Delta$ in order to obtain a series of graphs on which are made all subsequent
analyses. Here we are concerned with the impact of the chosen $\Delta$ on the
obtained graph series. We address the fundamental question of knowing whether a
series of graphs formed using a given $\Delta$ faithfully describes the
original link stream. We answer the question by showing that such dynamic
networks exhibit a threshold for $\Delta$, which we call the \emph{saturation
scale}, beyond which the properties of propagation of the link stream are
altered, while they are mostly preserved before. We design an automatic method
to determine the saturation scale of any link stream, which we apply and
validate on several real-world datasets.

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