  Contacts between individuals play an important role in determining how
infectious diseases spread. Various methods to gather data on such contacts
co-exist, from surveys to wearable sensors. Comparisons of data obtained by
different methods in the same context are however scarce, in particular with
respect to their use in data-driven models of spreading processes. Here, we use
a combined data set describing contacts registered by sensors and friendship
relations in the same population to address this issue in a case study. We
investigate if the use of the friendship network is equivalent to a sampling
procedure performed on the sensor contact network with respect to the outcome
of simulations of spreading processes: such an equivalence might indeed give
hints on ways to compensate for the incompleteness of contact data deduced from
surveys. We show that this is indeed the case for these data, for a
specifically designed sampling procedure, in which respondents report their
neighbors with a probability depending on their contact time. We study the
impact of this specific sampling procedure on several data sets, discuss
limitations of our approach and its possible applications in the use of data
sets of various origins in data-driven simulations of epidemic processes.
