Objectives:

The course provides an overview of how theoretical frameworks from different fields can be used to model and analyze complex social networks. Social network theory helps us understand the structure of the various social networks, how they evolve, how communication in social networks occurs, and how networks form the basis for interaction. The network terminology is central to many subjects, like economics, sociology, computer science, information science and mathematics. An interdisciplinary approach to social networking gives the possibility of analyzing common characteristics of seemingly disparate phenomena, from how information and behavior spreads in electronic social networks to how epidemics and financial crises develop, to how search engines utilize the html links between websites for ranking pages in a Web search. The huge amounts of data in applications today mean that efficient algorithms must be used.

The course will be taught jointly by the Departments of Informatics and Information Sciences.

On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:

After completing the course the student should be able to:

• demonstrate knowledge of theoretical models, concepts and results related to modeling and analysis of social networks.
• Reproduce, explain and demonstrate the most important mathematical models of social networks and social interaction.
• reproduce and explain the most important scientific results related to modeling of social networks.
• utilize different theoretical tools to analyze social networks.
• select between mathematical models apt to create an abstraction for a given type of phenomenon in a given social network.