This course provides an introduction to the field of social network analysis. Social network analysis is applied in different areas such as health, cyber security, information retrieval and communications. The focus of this course is on network analysis and theory. This course introduces the main structural concepts of social networks, and it combines theory and practice using programming. Students will explore several examples related to social network analysis. Students will apply NetworkX Python library in creating, manipulating, and study of the structure of social network.
Note: Students are responsible to both be aware of and abide by prerequisites for ICS courses for which they enroll, and will be administratively dropped from a course if they have not met prerequisites.First day attendance is mandatory.
4 Undergraduate credits
Effective May 2, 2018 to present
- Demonstrate an understanding of social network analysis theory and application.
- Distinguish the different types of social networks such as one mode networks, two modes networks, ego centric networks.
- Analyze social networks from different perspectives such as node level, group level and network level.
- Experiment with the different types of social network analysis measures and algorithms.
- Test and practice social network analysis using NetworkX library in Python