Fig. 8

Information spreading equality of real networks. Recall that we plot the spreading equality with low and high minority seeding portions. Each plot is a heatmap, where the x-axis represents the relative time t/T, the y-axis represents the different real-world networks, and the color represents \(\Delta I(t/T)\) while \(\Delta I(t/T) = 0\) represents equality. For Github, we find that initially \(\Delta I(t/T) < 0\) for high minority seeding portion and \(\Delta I(t/T) \approx 0\) for low minority seeding portion, indicating that majority nodes don’t have many advantage. This is because Github has the smallest minority portion, and this is consistent with the observation for influence on equality across different m values (see Fig. 5). Across all process settings, we find that APS takes the longest to reach equality, which is consistent with our previous observation that APS is less equal in degree and has a higher homophily level. DBLP is the most equal in information access, which is consistent with lower homophily. We find that the information access equality landscape depends on different process settings. For example, under asymmetric transmission rate, we notice that \(\Delta I(t/T)\) becomes positive for Github and DBLP under high seeding portion, which is not the case under symmetric transmission rate. We also find that achieving equality is much harder under complex contagion and asymmetric transmission rate