For those of you who like to delve into the research of networks a couple of articles, which were recently published in Science, might be interesting.
As I learned, scientists still “tend to describe how a complex system looks and behaves”, because it’s not clear what a complex system is exactly. So far researchers define it as something that “consists of many elements that interact so strongly that they tend to organize themselves in one way or another”. As a comparison: “A car may be complicated, but it is not a complex system, as each of its parts interacts with a few others in a predictable way. But cars in traffic form a complex system, as drivers’ jockeying for position can lead to surprises such as ‘phantom’ traffic jams that arise for no obvious reason”.
Some of the articles:
Reading “Predicting the Behavior of Techno-Social Systems” I learned about what brings us closer to achieving true predictive power of the behavior of techno-social systems and that there is the need for a “network” mindset. The article focuses on human interactions and mobility and talks about moving the analysis of networks from “small social groups” to the “quantitative analysis of social aggregate states”.
“Scale-Free Networks: A Decade and Beyond” talks about whether real networks as the society, the Internet, or the cell could function seamlessly if their people, nodes, or molecules, were wired randomly together.
“Revisiting the Foundations of Network Analysis” explores when a node is a node, standard frameworks, network processes and the choice of the right network presentation. Some of the key words for me: “reality mining”, which has been defined as the “collection of machine-sensed environmental data that are related to human social behavior”.