We investigate the nature of written human language within the framework of complex network theory. In particular, we analyse the topology of Orwell's 1984 focusing on the local properties of the network, such as the properties of the nearest neighbors and the clustering coefficient. We find a composite power law behavior for both the average nearest neighbor's degree and average clustering coefficient as a function of the vertex degree. This implies the existence of different functional classes of vertices. Furthermore we find that the second order vertex correlations are an essential component of the network architecture. To model our empirical results we extend a previously introduced model for language due to Dorogovtsev and Mendes. We propose an accelerated growing network model that contains three growth mechanisms: linear preferential attachment, local preferential attachment and the random growth of a pre-determined small finite subset of initial vertices. We find that with these elementary stochastic rules we are able to produce a network showing syntactic-like structures.
Masucci and Rodgers REF investigate the topology of Orwells 1984 within the framework of complex network theory.
Network properties of written human language
Phys Rev E.74. 026102, 2006
Mathematics Physics Medicine