This thesis consists of two parts. The first part describes the linear influence model which is used to analyze and predict the diffusion of information in the network. First, we provide motivation for this model, followed by a formal description of the model and finally we apply the model to the problem of diffusion of information in a network containing news published in the period from September 2008 to September 2009. In order to provide better understanding of the model, we give examples of other fundamental ways of modeling the diffusion in complex networks. For the purposes of this thesis, the first section provides basic concepts used to display and analyze networks. We explain the theoretical background of network construction, as well as many network’s properties that are used in its analysis. The second part is an analysis of the cooperation in the Japanese automotive industry, based on data from the years 1983, 1993 and 2001. For each of those years a cooperation network is built and they are compared to each other on a global scale, by observing changes in the basic properties of the network. In addition, we make a comparison at the node level, presenting which companies were influential in that period and how their influence changed over time. We provide an importance analysis for the company that has proven to be the most influential, and we compare the network damage caused by ejection of that company and of a randomly selected one. We show the influence network of that company, as well as the entire cooperation network without that company.