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**Introduction to Network Analysis (INA)**Networks or graphs are ubiquitous in everyday life. Examples include online social networks, the Web, wiring of a neural system, references between WikiLeaks cables, Supervizor, terrorist affiliations, LPP bus map, plumbing systems and your brain. Many such real-world networks reveal characteristic patterns of connectedness that are far from regular or random. Networks have thus been a prominent tool for investigating real-world systems since the 18th century. However, while small networks can be drawn by hand and analyzed by a naked eye, real-world networks require specialized computer algorithms, techniques and models. This led to the emergence of a new scientific field about 15 years ago denoted network analysis.

The course will first introduce the field of network analysis and highlight the differences between classical graph theory and modern network science. In the main part of the course, the students will learn about fundamental concepts and techniques for the analysis of real-world networks including node centralities and equivalence, graphlet counting, blockmodeling, community detection, role discovery, link prediction, network modeling and visualization. The last part of the course will be devoted to selected practical applications of network analysis in fraud detection, software engineering, information science and other.

The objective of the course is to present a broad spectrum of network analysis concepts and techniques, clarify their theoretical foundations and demonstrate their practical applicability. The topics covered were carefully selected thus to be suitable for a wide range of students and to serve as an introduction to more advanced network analysis courses like Selected Topics in Computer and Information Science: Social and Information Network Analysis (ASI).

Except for good programming skills in some general purpose language, there are no specific prerequisites for the course. However, the students will benefit from a solid knowledge in graph theory, probability theory and statistics, and linear algebra.

The course is offered in the summer semester starting on February 20th, 2017 and lasts for fifteen weeks. Lectures and practice will be held in either English or Slovene.

For more see eUcilnica.

- nosilec: Lovro Šubelj