As we increasingly live in a networked world, studying data that is shaped in the form of networks becomes an essential part of the toolkit of information researchers and data scientists. Social network analysis is a structural perspective to study the social world that focuses on the relationships between actors rather than the characteristics of the individuals themselves. It can be applied to a wide variety of social questions, and is used as a powerful method of research across various disciplines. The course offers a broader view of theory and applications of social network analysis, including applications to online and social media networks. We will learn how to identify influential actors within social networks, investigate community structure within networks, and test hypotheses to analyze how networked data can explain the social world. The course (INF2163H — Data Analysis of Social Networks) includes a practical component and provides hands on experience on networks data collection and analysis using social network analysis existing tools.
Note: Formerly a special topics course. Effective fall 2020, the course is a regular course.