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Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
EPPS 6355 (Overall) | |||||
A- | |||||
EPPS 6355 Rebecca Cordell | |||||
A | |||||
EPPS 6355 Vito D'Orazio | |||||
A- | |||||
EPPS 6355 Simon Fass | |||||
Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
EPPS 6355 (Overall) | |||||
A- | |||||
EPPS 6355 Rebecca Cordell | |||||
A | |||||
EPPS 6355 Vito D'Orazio | |||||
A- | |||||
EPPS 6355 Simon Fass | |||||
Machine Learning for Social Text Data
EPPS 6355
School of Economic, Political and Policy Sciences
This course explores methods for extracting and analyzing text as data. Automated text analysis has become widely used in the social sciences following recent innovations in machine learning and the increased digitalization of political texts. The course covers the theoretical foundations for text analysis and discusses the promises and challenges of analyzing text as data. Students will become familiar with different techniques for systematically analyzing text with applications to the study of political science topics. The focus of the course is on practical applications that allow students to apply cutting edge statistical and computational techniques to their own research. 3 credit hours.
Offering Frequency: Every two years
Grades: 33
Median GPA: A-
Mean GPA: 3.577
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Machine Learning for Social Text Data
EPPS 6355
School of Economic, Political and Policy Sciences
This course explores methods for extracting and analyzing text as data. Automated text analysis has become widely used in the social sciences following recent innovations in machine learning and the increased digitalization of political texts. The course covers the theoretical foundations for text analysis and discusses the promises and challenges of analyzing text as data. Students will become familiar with different techniques for systematically analyzing text with applications to the study of political science topics. The focus of the course is on practical applications that allow students to apply cutting edge statistical and computational techniques to their own research. 3 credit hours.
Offering Frequency: Every two years
Grades: 33
Median GPA: A-
Mean GPA: 3.577
Click a checkbox to add something to compare.