This course introduces the conceptual and practical tools that define the field of social network analysis. Some of the main analytical areas discussed include blockmodeling, multidimensional scaling, community detection, and statistical testing of network hypotheses. Substantive topics covered include how networks affect attitudes, preferences and behavior of people in organizations. By the end of the course, students acquire the basic skills needed to map out networks of social, economic and communication relations, diagnose features of networks that might help or hinder individual or team performance, and be able to recognize and describe the main features of network structure. Contemporary network research is unique in that its methodological tools derive directly from practical as well as theoretical concerns. For this reason, class time is allocated equally to methodological and substantive issues, with each substantive topic tied to specific analytical strategies. The course is based on a mix of lectures, workshops, hands-on computer exercises, and interactive examples of analysis of actual and simulated network data.
The final grade is calculated according to the following weighting scheme: Final exam: 50% (in class, closed book); Midterm exam: 20% (in class, closed book); Five Homework assignments: 20 % (due in class every week); Class participation: 10%.
The recommended text for this course is: Borgatti, S.P., Everett, M.G., and Johnson, C.J. 2013. Analyzing Social Networks. Sage Publications.
Free online resources
The course is potentially open to all students at USI. However, students enrolled in faculties other than Economics need will written permission from instructors before the beginning of the course.