A New Framework for ABMs Based on Argumentative Reasoning - Advances in Social Simulation - page 31

(a) NetArg model at time 0, with
bridges allowed in the caveman
graph.

(b) New opinions emerge from in-
teraction in dialogues at time 50.

Fig. 3. The distribution of extensions, at the population level, at time 0 and at time
50. In (b) it is evident the presence of newly formed extensions, not present at setup.

ties: does the presence of bridges lower polarization even with our argumenta-
tive agents? We set the AF s distribution fixed at 0.5 and allowed trust to take
values: 0, 0.2, 0.5, 0.8 and 1. Results are shown in Figure 4. Dialogues enhance
polarization because they give raise to new opinions sets, thus increasing opin-
ion distance among the agents. With no bridges connecting caves ( a ), each cave
quickly stabilizes at a local minimum. However, different caves will end up in
different local minima, which results in a high polarization overall. Trust is able
to lower the curve, but only until 0.8, because at 1 every agent changes her mind
continuously so that polarization is even enhanced. In a sense, agents with total
trust are “gullible” agents ready to believe anything. The instability arises if all
agents are gullible, because there is no stable opinion. On the contrary, when
bridges are present ( b ) polarization levels are lowered considerably. This time,
caves can receive information from other caves, and this “small-world” topology
lets the population exit from local minima. Increasing trust is more effective in
this case, and values as low as 0.5 are able to lower polarization nearly to 0.
We then control for different combinations of the two AF among the popula-
tion, along with different level of trust. We can conclude that the model fits the
predictions of Granovetter's theory: (1) the presence of bridges between caves
fosters agreement and consensus, increasing the number of “like-minded” agents
and (2) since only caves with bridges to other caves can receive new information,
only connected caves learn new relations between arguments and change their
minds.
In the second experiment we want to test if “majority wins”, or if one AF is
more “invasive” that the other, controlling for different distribution of the AF s
among the agents. We distributed AF 1 among agents with different probabilities
(0.2, 0.4, 0.6 and 0.8), controlling for different level of trust (0.2, 0.5 and 0.8). We
replicated the experiment with and without bridges. Results are shown in Figure
5. In ( a ) no bridge is allowed, neither AF 1 (in white) nor AF 2 (in black) lose
their positions (see the percentage for the initial distribution) to a significant
extent. In ( b ) bridges are allowed, and the jump toward blacks is quite evident: