Predicting the Robustness of Large Real-World Social Networks Using a Machine Learning Model

Figure 1

Computation time of a complete Monte Carlo network node attack simulation for all studied real-world social networks (using initial betweenness (IB) and recalculated degree (RD) attack strategy) and for 4 networks (using recalculated betweenness strategy (RB)) as a function of the product N × E (node number (N) edge number (E). We found that tIB and tRD scale approximately linearly with respect to the product N × E, while tRB scales linearly with respect to the product N² × E (insert graph). From this result, we can estimate that the RB simulation time for the largest networks in our dataset will take more than 50 days using the same hardware.