Figure 5
Causal Networks. (a) Graph showing the maximal causal effects between the activity of the IRA nodes and the supporting classes of the presidential candidates. Arrows indicate the direction of the maximal causal effect (≥0.16) between two activity time series. The width of each arrow is proportional to the strength of the causation, and the size of each node is proportional to the auto-correlation of each time series. Dark blue and dark red highlight the contribution of strong Clinton and Trump supporters, respectively. Light blue and light red are associated with the weak Clinton and Trump supporters, gray with the undecided users, and orange with the IRA nodes. The causal relation primarily flows from strong supporters of both Trump and Clinton to weak and strong supporters of opposing political candidates. Additionally, weak supporters from both sides play a role in influencing the undecided group, with weak Trump supporters receiving support from strong Trump supporters in their efforts. Notably, IRA nodes do not play a significant role in this causal network, suggesting that they have limited influence on shaping Twitter discourse. (b) Graph showing the maximal causal effects between the activity of the suspended nodes and the supporting classes of the presidential candidates. Arrows indicate the direction of the maximal causal effect (≥0.2) between two activity time series. Strong Trump supporters have a causal effect on Suspended nodes, which, in turn, have a causal influence on both weak supporters and the undecided group. Additionally, weak supporters continue to exert a causal effect on the undecided group. Strong Trump supporters have a causal effect on strong Clinton supporters, but not vice-versa