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With the boom of social networks, the need for understanding the dynamics of these systems resulted in social network analysis tools to be at the interest of many parties. SNA provides a set of techniques for analyzing the underlying graph to reveal the structures (if any) existing in a network (also anything represented as a network) via measuring the relationships among the nodes and the individual characteristics of the nodes.

Since networks are the realizations of the mathematical structure represented as graphs, network analysis is in fact analysis of the underlying graph structure. Graphs are powerful mathematical abstractions to represent a system with inter-connections and interactions. There are compact metrics summarizing a graph’s structure that maps to the interactions among the nodes - vertices of the graph. This seminar starts with an overview of these metrics as well as basics of social networks and covers the use of these metrics for the design and analysis of networks, e.g. ad hoc networks, delay tolerant network, and content centric networks. 

At the end of the seminar, students are expected to have a clear understanding of basics of SNA (e.g., centrality measures, community finding algorithms) and their application to communication/data networks as well as all steps of research (reading, writing, reviewing, revising). Students are expected to have completed Scientific Writing class. 

The seminar will be in English.