Social Network Analysis with Focus on Behavioral Patterns

Abstract

The doctoral thesis deals with social network analysis with the focus on users’ behavioural patterns. The main goal is to propose a new methodology for analysis of users’ behaviour in the systems, which store users’ activities into log files. The aim is to find user groups with similar behaviour and latent ties between them to clearly present their behaviour in the system. The proposed approach consists of several steps; each of them required a solution of specific problems. The solutions were done using principles from business process analysis, log mining, complex network analysis, data mining, artificial intelligence and graph theory. The proposed methodology has been tested through several experiments performed within three spheres: e-learning systems, website analysis and simulation modelling. The proposed methodology can be used in several spheres for the optimisation of system structures, in recommended systems, for student/user management, for marketing purposes, etc.