Social Network Analysis

3 Credits · Level: Graduate, Undergraduate

Social Network Analysis (SNA) allows patterns in relationships to be graphed and explored. Whether tracking the flow of information or influence, SNA provides a valuable tool for uncovering the important implications of relationships and social structures. This class balances theory and practice, concepts and computations. The goal of this course is to enable students to conduct SNA research of their own. Students will learn how SNA is currently being used; applications that include the analysis of politics, social media, and disease transmission, among others. Hypothesis testing is a major topic for this course. Students will gain matrix manipulation skills and data management skills. Students will also learn how to graph relationships given a set of data and the mathematical techniques that unearth key pieces of information in these graphs. Data collection methods and ethics will be explored. Strategies for efficient coding and data entry are key aspects of the course that aim to build practical skills. Students will learn relevant mathematical techniques in a supportive, highly verbal manner. Students will also learn computer-based SNA techniques using R and R Studio. These skills will assist students in completing research projects throughout the course of the semester.