  We propose a new method for aggregating the information of multiple reviewers
rating multiple products. Our approach is based on the network relations
induced between products by the rating activity of the reviewers. We show that
our method is algorithmically implementable even for large numbers of both
products and consumers, as is the case for many online sites. Moreover,
comparing it with the simple average, which is mostly used in practice, and
with other methods previously proposed in the literature, it performs very well
under various dimension, proving itself to be an optimal trade--off between
computational efficiency, accordance with the reviewers original orderings, and
robustness with respect to the inclusion of systematically biased reports.
