Teaching Assistant Experience

COMM 1: Introduction to Communication (Undergraduate lecture; Instructor: Prof. Jeff Hancock)

  • Feedbacks from my students:
    “Yingdan was great: very knowledgeable and wants her students to be successful in the class.”
    “Yingdan’s willingness to model the section based off our feedback was really great. She really tried to make each section the most helpful for us as possible.”
    “Yingdan was always available and willing to answer questions. She always tried her best to make sure we understood the material.”

COMM 106/206: Communication Research Methods (Undergraduate/graduate seminar; Instructor: Dr. Anna Gibson)

  • Feedbacks from my students:
    “I think [of Yingdan] as a person to lean on when I didn’t know what I was doing.”
    “Yingdan would reply to emails relatively promptly, and this immediacy of feedback/faster access to info helped my learning process.”
    “The R sessions were really helpful, redevelop some of the fundamentals that I had lost over the years.”

Guest Lecture Experience

Rethinking User Engagement with Screens
Social Media Analytics, University of Wisconsin–Madison

Competing for Attention: How the Chinese Government Uses Social Media for Propaganda
Persuasive Technologies, University of California, Davis

Video-as-Data in Computational Social Science
Introduction to Computational Social Science, 2022 Summer School in Applied Social Science Research Methods, NYU-Shanghai

Rethinking Life on Screens: Measuring Smartphone Activities Through Screenomics
Social Media Analytics, University of Wisconsin–Madison

Capturing Clicks: How the Chinese Government Uses Clickbait to Compete for Visibility
Social Media Analytics, University of Wisconsin–Madison

Capturing Clicks: How the Chinese Government Uses Clickbait to Compete for Visibility
Natural Language Processing, University of San Francisco

Image as Data: Automated Visual Analysis in Studying Digital Media
Comparative Journalism Studies, Tsinghua University

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.

Video-as-Data Research Methods
As video-based social media platforms such as YouTube and TikTok have become a hallmark of today’s social media landscape, the abundant video data and the outperforming persuasive effects of video than text have prompted me to quantitatively analyze large-scale video data. If you are interested in video-as-data research methods, these resources could be helpful:

  • My lecture slides for “Video-as-Data in Computational Social Science” guest lecture: in this lecture, I introduced why and how we can quantitatively analze videos. I used my own research to illustrate how videos can be analyzed frame by frame, and what visual, auditory, and textual features can be extracted from videos.
  • Replication files for “The Pervasive Presence of Chinese Government Content on Douyin Trending Videos” published in Computational Communication Research: This repo includes my code for computing video brightness, video color complexity, faces, warm color dominance, and cold color dominance.

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: