Yingdan Lu

Assistant Professor
Department of Communication Studies
School of Communication
Northwestern University
Email: yingdan [at] northwestern.edu

Current Teaching at Northwestern University

COMM_ST 379 / POLI_SCI 390: Digital Propaganda and Repression (Undergraduate lecture) [syllabus available upon request]
Digital media and technologies, often considered liberation technology, have increasingly been employed by governments and non-political entities for political propaganda and repression. This course will examine the practices and implications of propaganda and repression within the digital media landscape. We will explore the role of digital media and technologies in authoritarian regimes, the common strategies and applications of digital propaganda and repression, and consider how various actors implement these tactics, along with their consequences and global impacts. Through course readings, in-class discussions, and student-led projects, students will develop a critical understanding of the interplay between digital media, politics, and civil society.

MTS 525: Computational Communication Research (Ph.D. seminar) [syllabus available upon request]
Digital technologies have prompted communication researchers to leverage massive digital datasets and computational tools to better understand the digital social environment. This research seminar offers an overview of key computational methods in social science research, with a focus on computational content analysis of large-scale digital data. We will explore main methods and techniques for digital data collection, machine learning, and the analysis of large-scale textual, visual, audio, and multimodal data. The course also examines current opportunities and challenges arising from recent computational breakthroughs, such as large language models (LLMs). Through engagement with key scholarship, hands-on programming tutorials, and research projects, students will gain a conceptual understanding of computational methods, receive practical training in integrating computational tools into their research, and develop a critical perspective on computational communication research.

Previous Teaching

COMM 1: Introduction to Communication (Undergraduate lecture; Teaching assistant for Jeff Hancock)

COMM 106/206: Communication Research Methods (Undergraduate/graduate seminar; Teaching assistant for Anna Gibson)

Teaching Resources

R Programming for Beginners
R is a functional open-source programming language widely used in statistical analysis and visualization. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. Similar to any programming language, learning R may not be easy at the beginning, but once you get into it, you can explore more powerful things with R. If you are interested in learning R programming, these resources could be helpful:

  • Getting started with R/RStudio: I wrote this instruction for my students in the course Communication Research Methods at Stanford University. In this instruction, you will find more details on how to install R and Rstudio, and some useful resources to help you familiarize with R.
  • R practice code for beginners: This code is based on my teaching materials for the course Communication Research Methods at Stanford University. If you are a beginner to R programming, you can run this R code line by line in the R console (bottom left quadrant in R Studio) and learn from setting work directory to creating simple plots.
  • Swirl: Swirl is an interactive R package that helps beginners to learn R programming and data science through a fun way. You can install swirl package in your RStudio by following the instructions. By Swirl, you can work through short lessons to start writing R codes.

Books that I Will Recommend
Here are some books that I would recommend for people who want to systematically learn quantitative social science research and computational social science research: