Figure 1From: Social dynamics of financial networksTime series of daily networks. (a) Daily time series of the number of edges M (upper) and the number of banks N (lower). Most of the downward spikes in N and M are due to the national holidays in Italy. (b) Visualization of the largest (left), a middle-sized (middle) and the smallest (right) daily networks (visualized by graph-tool [65]) (c) Time series of bipartivity. Bipartivity is a measure of bipartite structure defined as \(\sum_{i=1}^{N}\cosh (\hat{\lambda}_{i})/\sum_{i=1}^{N}\exp (\hat{\lambda}_{i})\), where \(\{\hat{\lambda}_{i}\}\) denotes the eigenvalues of the adjacency matrix. The bipartivity measure takes 1 if the network is fully bipartite and 0.5 if a complete graph [66]. Since the bipartivity is defined for undirected graphs, we ignore the directionality of edges. Black line represents the moving average with 20-day smoothing windowBack to article page