Course Description:
This graduate-level course serves as an introduction to advanced methods for the study of communication. The course focuses on three core areas: computational methods and big data, bio- and psycho-physiological methods, and emerging applications of artificial intelligence, including transformers and large language models (LLMs). Students will explore how new forms of data and new analytical techniques are reshaping communication research. By the end of this course, students will have a comprehensive understanding of these cutting-edge methodologies and their implications for the study of communication and adjacent social scientific domains.
Objectives
Upon completion of this course, students should be able to accomplish the following objectives:
- Understand and critically evaluate advanced research methods in communication, including computational approaches, big data analytics, bio- and psycho-physiological techniques, and AI-based methodologies, articulating their foundations, applications, strengths, and limitations.
- Apply knowledge of these methods to design studies that address complex communication phenomena, demonstrating the ability to integrate multiple approaches and consider ethical, pragmatic, and other implications.
- Analyze and interpret data generated from these advanced research methods, drawing conclusions about communication processes and effectively communicating these conclusions and their implications for communication theory and practice.
This class will combine lectures, readings, hands-on data analysis exercises, and group discussions.