Master thesis: Growth and Self-Organization Processes in Directed Social Network

Abstract

Large dataset collected from Ubuntu chat channel is studied as a complex dynamical system with emergent collective behaviour of users. With the appropriate network mappings we examined wealthy topological structure of Ubuntu network. The structure of this network is determined by computing different topological measures. The directed, weighted network, which is a suitable representation of the dataset from Ubuntu chat channel is characterized with power law dependencies of various quantities, hierarchical organization and disassortative mixing patterns. Beyond the topological features, the emergent collective state is further quantified by analysis of time series of users activities driven by emotions. Analysis of time series reveals self-organized dynamics with long-range temporal correlations in user actions.