This course provides the students with relevant topics in network analysis, from social networks to information and technological networks such as the Internet. We will present and revisit some important concepts on graph theory as well as discuss network science as an important tool for understanding several processes that pervade our daily lives. The course goals are to introduce basic concepts in network theory, to discuss metrics and models and to use software analysis tools for analyzing a wide variety of real-world network data.

Content

The course is structured in three parts.

• The first part of the course covers the main concepts of graph theory and social networks.  The main goal is to introduce the basic graph definitions such as centrality measures, path and connectivity as well as the most traditional graph models applied on network science: random graphs, small-world model and Barabasi-Albert model. Furthermore, we will discuss how relationships between individuals impact community formation (homophily), structural balance (positive and negative relationships) and triadic closures (the role of strong and weak ties) on social networks.
• The second part explores network dynamics. We will focus on how information flows in our society, both from a population model view (following the crowd approach) as well as structural model view (cascading behavior and small-world approaches). We will discuss the role of social capital on these processes.  At the end, we will explore some epidemiological models, and how relationships and individual’s behavior can potentialize the spread of the diseases.
• The third part covers information networks and World Wide Web. Students will learn more about PageRank and Hits algorithms. We will also introduce the first model of the structure of the web, known as Bow-Tie model.

The assessment will be based on a research project developed by teams including two or three students. The evaluation of projects will be based on the produced report, following a scientific paper format.  In alternative, students can focus on a specific topic introduced during the course and provide a report on recent advances proposed in the state of the art.