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The large-scale distribution of galaxies is generally analysed using the two-point correlation function. However, this statistic does not capture the topology of the distribution, and it is necessary to resort to higher order correlations to break degeneracies. We demonstrate that an alternate approach using network analysis can discriminate between topologically different distributions that have similar two-point correlations. We investigate two galaxy point distributions, one produced by a cosmological simulation and the other by a Lévy walk. For the cosmological simulation, we adopt the redshift z = 0.58 slice from Illustris and select galaxies with stellar masses greater than 10⁸ M_⊙. The two-point correlation function of these simulated galaxies follows a single power law, ξ(r) ∼ r^−1.5. Then, we generate Lévy walks matching the correlation function and abundance with the simulated galaxies. We find that, while the …