SOC 6610
Last Updated
- Schedule of Classes - June 7, 2023 8:54PM EDT
- Course Catalog - June 7, 2023 7:14PM EDT
Classes
SOC 6610
Course Description
Course information provided by the Courses of Study 2022-2023.
This is a course on networks and text in quantitative social science. The course will cover published research using text and social network data, focusing on health, politics, and everyday life, and it will introduce methods and approaches for incorporating high-dimensional data into familiar research designs. Students will evaluate past studies and propose original research.
When Offered Fall.
Prerequisites/Corequisites Prerequisite: HD 6760 or GOVT 6029 or SOC 6020 or equivalent.
Outcomes
- Learn to critically evaluate empirical research that uses text as data or social network analysis.
- Connect fundamentals of research design to high-dimensional data analysis.
- Develop verbal and written skills via in-class discussion, presentations, and written assignments.
- Learn to represent complex relationships quantitatively and conduct high-dimensional data analyses using statistical programming.
- Learn methods for avoiding over-fitting in high-dimensional data analysis.
Regular Academic Session. Combined with: GOVT 6619, HD 6610, INFO 6610
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Credits and Grading Basis
3 Credits Opt NoAud(Letter or S/U grades (no audit))
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Class Number & Section Details
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Meeting Pattern
- R M Van Rensselaer Hall 1102
- Jan 23 - May 9, 2023
Instructors
Hobbs, W
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Additional Information
Instruction Mode: In Person
Restricted to PhD students. Other students may be considered on a case-by-case basis by permission of instructor.
Regular Academic Session. Combined with: GOVT 6619, HD 6610, INFO 6610
-
Credits and Grading Basis
3 Credits Opt NoAud(Letter or S/U grades (no audit))
-
Class Number & Section Details
-
Meeting Pattern
-
R
Bloomberg Center 497
Cornell Tech - Jan 23 - May 9, 2023
Instructors
Hobbs, W
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R
Bloomberg Center 497
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Additional Information
Instruction Mode: Distance Learning-Synchronous
Taught in NYC. Enrollment limited to Cornell Tech Students.
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