This course provides an introduction to computational methods in textual analysis, specifically designed for those in the field of communication research. This course is practical and hands-on in nature and focuses on theoretical and empirical questions we can ask with text-as-data from a social science perspective and learn how to answer them. The course contentcovers data scraping, text data cleaning and preprocessing, dictionary- based analysis, unsupervised topic modeling, supervised text classification, the use of large language models, and techniques for ieffective visualization and reporting of findings. Basic Python or R knowledge would be beneficial, but advanced programming skills not needed.

Prerequisites: Graduate standing; consent of department for students outside of COMM.

4

Units

Optional

Grading

1, 2, 3

Passtime

Graduate students only

Level Limit

Letters and science

College
These majors only comm
LIU JIAYING
No info found
Lecture
SSMS 1009
W
14:00 PM - 16:50 PM
14 / 15
COMM 593A
0 / 15 Enrolled
Directed Reading
T B A
COMM 596A
0 / 15 Enrolled
Directed Research
T B A
COMM 597
0 / 30 Enrolled
Preparation for the Qualifying Examination
T B A
COMM 598
0 / 30 Enrolled
Master's Thesis Research and Preparation
T B A
COMM 599
0 / 20 Enrolled
Dissertation Preparation
T B A