|Keywords:||Engineering and Technology; Teknik och teknologier; Masterprogram i tillämpad beräkningsvetenskap; Master Programme in Computational Science|
|Full text PDF:||http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-251289|
Population of earth is increasing rapidly, generating more and more situations which allow us to study the mechanisms behind humans. Previous studies have found evidence of important network effects. When network effects are present, the value of a product or service is dependent on the number of others using them; however there is a lack of empirical research concerning them. The goal of this thesis is to examine and analyze such networks and try through a simulation model of a diffusion process to identify the determinant that can predict the result. We investigate these networks in terms of the probability of the virus to be spread to the neighbors of the receiver needed to reach a given percentage of the nodes in the network. Moreover, we are going to answer to questions like how these parameters change when we change the structure of the networks and their relationships. Finally, the provided results after a number of tests performed on our data will demonstrate how they effect in networks. The study of previous literature will help us to obtain a more depth understanding of multilayer networks. Verification of the model on real data is an objective of the thesis but it is not guaranteed, given the difficulty in retrieving real data.