Figure 2.

Empirical correlations between individual-level properties. We divide the spreading events into six consecutive non-overlapping periods. The date on the x axis represents the starting date of each period. In each period, we reconstruct individual influence and susceptibility via the IS algorithm, and measure the Spearman’s correlation coefficients, ρ, between the indegree (kⁱⁿ), outdegree (k^out), influence () and susceptibility (). Only those value pairs where both values are not equal to 0 are conserved. Filled markers denote correlation values that are significantly larger or smaller than the correlation values calculated on randomized networks (P < 0.05; see Note S4 for details); open markers denote correlation values that do not significantly differ from the correlation values calculated on randomized networks (P > 0.05). The strongest consistent empirical correlation is that between the outdegree (k^out) and influence (); the other correlations are weak or non-significant.