  Many networks in natural and human-made systems exhibit scale-free properties
and are small worlds. Now we show that people's understanding of complex
systems in their cognitive maps also follow a scale-free topology (P_k =
k^-lambda, lambda [1.24,3.03]; r^2 <= 0.95). People focus on a few attributes,
as indicated by a fat tail in the probability distribution of total degree.
These few attributes are related with many other variables in the system. Many
more attributes have very few connections. The scale-free properties in the
cognitive maps of people arise despite the fact that their average distances
are not different (Wilcoxon sign-rank test, W=78, p=0.75) than random networks
of the same size and connection density. The scale-free property manifests
itself in the higher hierarchical structure compared to random networks
(Wilcoxon sign-rank test, W=12, p=0.03). People use relatively short
explanations to describe systems. These findings may help us to better
understand people's perceptions, especially when it comes to decision-making,
conflict resolution, politics and management.
