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This dataset contains generated small‑world graphs and their topological analyses, intended for studying how short‑range and long‑range connections differently modulate the dynamics and states of small‑world networks.

This dataset is designed for one‑to‑many graph translation tasks. The graphs have no node features; the goal is to learn a mapping from input graph topology to target graph topology. Each input graph is a directed scale‑free network with a power‑law degree distribution. For target graph generation, a node is selected as the target node with probability proportional to its indegree and connected to a new source node with probability 0.41. Similarly, a source node is chosen proportional to its outdegree and connects to a new target node with probability 0.54. Then, m edges (where m equals the number of input nodes) are added between the two nodes to form the target graph. Hence both input and target graphs are directed scale‑free graphs.