Fig. 2: The series of networks depicts the gradual transformation of a sparse network into a highly connected graph due to the accumulation of observational errors.
From: Assessing the impact of sampling bias on node centralities in synthetic and biological networks
The node size represents the node’s connectivity, illustrating how observation errors can significantly alter network architecture. In (a) edges are added to the initial network randomly. In (b) highly connected nodes are more likely to receive new edges, while in (c), lowly connected nodes are more likely to receive additional edges.
