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Course 2015-2016 a.y.

30389 - SOCIAL NETWORK ANALYSIS (Introduction to Network Science)


CLEAM - CLEF - CLEACC - CLES-BESS - BIEMF
Department of Management and Technology

Course taught in English


Go to class group/s: 31

CLEAM (6 credits - II sem. - OP  |  SECS-P/10) - CLEF (6 credits - II sem. - OP  |  SECS-P/10) - CLEACC (6 credits - II sem. - OP  |  SECS-P/10) - CLES-BESS (6 credits - II sem. - OP  |  SECS-P/10) - BIEMF (6 credits - II sem. - OP  |  SECS-P/10)
Course Director:
GIUSEPPE SODA

Classes: 31 (II sem.)
Instructors:
Class 31: GIUSEPPE SODA


Course Objectives
This course provides an intensive introduction to the field of social network analysis. The course is divided in class-lecture sessions and lab-exercise sessions. The objective is to familiarize students with the theory, research, methodological issues, and practical implications connected with social network analysis. Upon completion of the course, students should have a good grasp of social network concepts and methods, and be able to use them.The course covers theory, concept and method as well as hands-on application in the lab-sessions. The purpose of the lab-sessions is to teach how to actually analyze social network data. This means mastering the software tools as well as analytical strategies. Students will need to bring their own laptop in order to effectively participate in the lab. Network concepts covered will include graph-theoretic fundamentals, centrality, cohesion, subgroups, equivalence. Theoretical areas will include embeddedness, social capital, organizational learning and organizational governance. This perspective will be integrated with a practitioner perspective by using examples from consulting engagements.

Course Content Summary
PART I:
Introduction to network science; Network structures: understanding social networks; Using graphs to represent social relations; Creating network data; Visualizing networks; Using matrices to represent social relations; Working with network data; Connection; Embedding; Ego networks; Centrality and power; Cliques and sub-groups; Positions and roles: The idea of equivalence; 16. Multiplex networks; Two-mode networks; Big networks; Small world networks; Scale free networks.

PART II:
Network origins; Network consequences; Network processes: Contagion; Diffusion; Influence; Network dynamics.

PART III:
Applications of Social Network Analysis: intra-organizational communities and firms; strategic alliances and mergers & acquisitions

Detailed Description of Assessment Methods
For Attending Students:
Class contribution (exercises, class discussion, and, of course, attendance and punctuality): 40%;
Final written exam (test on the use of network data and their applications) 60%
R.A. Hanneman, M. Riddle: Introduction to social network methods. Available on line at http://faculty.ucr.edu/~hanneman/nettext/
G.Soda (ed) “Introduction to Network Science”, Il Pellicano, EGEA, 2014.

For Not Attending Students:
Final written exam (test on the use of network data and their applications) based on

Textbooks
  • R.A. Hanneman, M. Riddle: Introduction to social network methods. Available on line at http://faculty.ucr.edu/~hanneman/nettext/
  • G.Soda (ed) “Introduction to Network Science”, Il Pellicano, EGEA, 2014.

Prerequisites
Fluent in English;
The teaching method requires the use for the lab-sessions of the personal computer. The completion of exercises is an important aspect of the class, and will help them to familiarize with the UCINET software that includes the standard tools used in organizational network analysis.
All students are required to download on their PC the latest version of UCINET (www.analytictech.com).
Last change 14/05/2015 16:41