Computational Analysis of Media Content
Featuring Victor (Syuan-Li) Renn • Hosted by Yuqi Liang
What We'll Cover
1. A method that matters (30 min)
Our speaker will introduce one of the most important and useful methods in his field, and it will be presented in a clear and accessible way.
2. A 30-minute roundtable discussion between the speaker and the host
The topics are rarely covered in regular academic talks:
• Life journey: Why from National Taiwan University to UIUC? Why from Computer Science to Communication?
• What it's really like to do a PhD: insights, challenges, and lessons learned.
• Why think about careers beyond academia? What other possibilities can we explore?
• What would you do differently if given a second chance?
Speaker Information
Presenter: Victor (Syuan-Li) Renn
Ph.D. Student, Department of Communication, University of Illinois at Urbana-Champaign
Victor's research uses computational text analysis to examine how different forces influence the news production process in traditional media, and through what mechanisms these forces exert temporary or enduring effects on the resulting news content.
Moderator: Yuqi Liang
PhD Candidate, Department of Sociology and Institute for New Economic Thinking, University of Oxford
Yuqi's research focuses on developing methodologies in quantitative and computational social science, and applying them in life course and inequality studies. She develops two Python packages: Sequenzo for sequence analysis, and GLM Plus for extended generalized linear models.