Information Technology Reference
In-Depth Information
Algorithm 1.
Simulate an iteration of the model.
Require:
N
I
>
0
{N
I
is the number of iterations
}
Require:
N
A
>
0
{N
A
is the number of agents
}
for
I
=1
→ N
I
do
for
A
=1
→ N
A
do
select
a random agent
B
within
A
's neighbors
initiate dialog
with
B
end for
record
statistics
end for
This opinion revision process gives raise also to a polarization effect at the
population level. By polarization we mean that a population divides into a small
number of factions with high internal consensus and strong disagreement between
them. A perfectly polarized population contains two opposing factions whose
members agree on everything with each other and fully disagree on everything
with the out-group.
Using a modified version of the measure used by Flache & Macy [13], we
measure the level of polarization
P
at time
t
as the variance of the distribution
of the
AF
distances
d
ij,t
:
i
=
N,j
=
N
1
γ
t
)
2
P
t
=
(
d
ij,t
−
N
(
N
−
1))
i
=
j
where:
-
N
represents the number of agents in the population;
-
d
ij,t
represents the
AF
distance between agents
i
and
j
at time
t
, i.e., the
fact that agent
i
has an argument in her extension (
i
E
) while the other does
not, averaged across all available arguments (
|A|
):
d
ij
=
|
i
E
\
j
E
∪
j
E
\
i
E
|
;
|A|
-
γ
t
represents the average distance value at time
t
.
In the next section, we present and discuss the results of three experiments made
with NetArg.
5 Experimental Results
We present here the results of three different experiments that make use of the
AF
s in Figure 2. Each parameters combination has been ran 30 times and plots
display averaged values for each combination. The first experiment that we dis-
cuss aims at testing if the model can reproduce Granovetter's theory about weak
