Courses at MSU

Communication Research Design II

Graduate course, Michigan State University, Department of Communication, 2023

This course is the second in the Ph.D. statistics sequence at the Department of Communication, MSU. It has a prerequisite of COM 901 or its equivalent. It is a four-credit class. The course aims to provide PhD students with a working knowledge of the assumptions, concepts, and theories underlying the most frequently used multivariate analysis techniques in quantitative social and behavioral sciences. These techniques include, but are not limited to, multiple regression, exploratory and confirmatory factor analysis, path analysis, structural equation modelling (SEM), multilevel analysis, and time series analysis. The selection of specific topics may be tailored to students’ research needs. The focus will be on practical issues such as selecting the appropriate analysis, preparing data for analysis in the popular statistical tools (e.g., SPSS, AMOS, or R), interpreting output, and presenting results of a complex nature. This course is a mixture of lectures, discussions, and hands-on practices.

Computational Social Science: Principles and Applications

Graduate course, Michigan State University, Department of Communication, 2022

Computational thinking and methods have been widely discussed and adopted by social scientists in various subject areas (e.g., anthropology, communication, political science, public health, and sociology). This course is about how computational social science (CSS), as an emerging paradigm of research, changes the way in which social scientists empirically observe and understand human society. The course is composed of three modules:

• The first module focuses on the fundamental principles in CSS, including research design, implementation, data collection and management, and data analysis.
• The second module focuses on the conceptualization and modeling of three types of data preeminent in CSS research: text, time, and structure.
• The third module concentrates on the application of computational methods in some prominent research domains, such as health communication, political communication, and user analytics.