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Curricular information is subject to change
Students who have finished this module are well-positioned to apply automated text analysis methods in their own work. They will have learned how to extract useful quantities of interest from text using the R statistical language, evaluate the outcomes and write up the results of an analysis that uses automated text analysis. Furthermore, students will be able to critically evaluate (social science) research that uses automated text analysis methods.
|Student Effort Type||Hours|
|Autonomous Student Learning||
Not applicable to this module.
|Description||Timing||Component Scale||% of Final Grade|
|Assignment: Coding assignments||Throughout the Trimester||n/a||Graded||No||
|Continuous Assessment: Research paper||Week 12||n/a||Graded||No||
|Presentation: Presentation of research paper||Unspecified||n/a||Graded||No||
|Resit In||Terminal Exam|
• Feedback individually to students, post-assessment
Feedback will be provided to students within 20 working days of the deadline for the assignment in accordance with university policy.
|Computer Aided Lab||Offering 1||Week(s) - 18, 19, 20, 21||Fri 13:00 - 14:50|
|Computer Aided Lab||Offering 1||Week(s) - 22, 23, 24, 30, 31||Fri 13:00 - 14:50|
|Computer Aided Lab||Offering 1||Week(s) - 27, 29, 32, 33||Fri 13:00 - 14:50|