The identification of signals from spontaneous reporting systems plays an important role in monitoring the safety of medical products. Network analysis (NA) allows the representation of complex interactions among the key elements of such systems. We developed a network for a subset of the US Vaccine Adverse Event Reporting System (VAERS) by representing the vaccines/adverse events (AEs) and their interconnections as the nodes and the edges, respectively; this subset we focused upon included possible anaphylaxis reports that were submitted for the H1N1 influenza vaccine. Subsequently, we calculated the main metrics that characterize the connectivity of the nodes and applied the island algorithm to identify the densest region in the network and, thus, identify potential safety signals. AEs associated with anaphylaxis formed a dense region in the 'anaphylaxis' network demonstrating the strength of NA techniques for pattern recognition. Additional validation and development of this approach is needed to improve future pharmacovigilance efforts.