Complex and social network analysis in Python
[EuroPython 2012] E Franchi - 3 JULY 2012 in "Track Ravioli""/>
A complex network is a network that has non trivial topological properties, i.e., properties hinting the presence of elaborate relationships among the actors, opposed to simple networks such as regular lattices or random graphs. Examples of complex networks are most social, technological or biological networks, such as the internet, the web, a professional network, the nervous system of an animal or the contact network of any social networking system. Network analysis has many practical applications, e.g., ranking or grouping items on the basis of their position in the network, and is also the basis of some collective intelligence and data mining techniques. Recently network analysis is also applied to security problems in the form of trust networks. Along with the basic concepts, working Python code is presented, both using existing network analysis Python tools and numeric packages. The focus is mainly placed on code, which will be shown and discussed together with the theory, with the idea that running code and simulations are easier to understand that formal maths. Since complex network datasets are typically huge, some high-level optimization techniques are also discussed. Although formulas are kept at the minimum, some maths skills are required along with basic knowledge of the Python programming language.