Text data are increasingly abundant in social science research, yet they are often underutilized in analysis. In this workshop, I will demonstrate how to conduct structural equation modeling (SEM) using both quantitative and qualitative data. The session will begin with an overview of SEM, covering its fundamental concepts and applications. Next, I will explore various approaches to extracting insights from text data, including dictionary-based methods, AI-driven sentiment analysis, and word embeddings. Following this, I will discuss how to integrate text data with other data types within the SEM framework. To illustrate these methods, I will use teaching evaluation data as a case study. Finally, I will showcase how to use the R package TextSEM and the online application BigSEM, developed in my lab, to conduct SEM with text data. Participants will leave the workshop equipped with practical tools and techniques for harnessing the potential of text data in their research.
- Instructor: Johnny Zhang