Admission requirements
Students are encouraged, but not required, to take Hacking the Humanities before this course.
Auditors are welcome, space permitting. Please note Students of the Minor Digital Humanities have priority. Students from other programmes can only be admitted if there are places left. Students from other programmes interested in taking this course are kindly requested to contact the Coordinator of Studies and the Lecturer, if you are interested in taking this course but NOT a student of the minor Digital Humanities. See also under registration below.
Description
In this course students will work on techniques used in text analytics, including POS tagging, n-gram analysis and machine learning. We will look into several case studies, in which these methods are applied in literary research, forensics, and social media analysis. In order to gain hands-on experience, students will work on the project of their choice and apply learned techniques. This course is designed as a continuation of the Hacking the Humanities course offered in the first semester. However, students who didn’t take Hacking the Humanities course are welcome.
Course objectives
The course will introduce students to advanced text mining and visualization techniques used in text analytics. By the conclusion of the course, students will have acquired skills that will allow them to design stream-lined projects that process, animate, map, and visualize a large corpus of texts.
Timetable
Please visit MyTimetable
Mode of instruction
Seminar
Attendance and active participation are obligatory for seminars. Students are required to prepare for and attend all sessions. The convenor needs to be informed without delay of any classes missed for a good reason (i.e. due to unforeseen circumstances such as illness, family issues, problems with residence permits, etc.). In these cases it is up to the discretion of the convener(s) of the course whether or not the missed class will have to be made up with an extra assignment. The maximum of such absences during a semester is two. Being absent without notification and/or more than two times can result in exclusion from the term end exams and a failing grade for the course.
Assessment method
Assessment
Assignments: 20 percent
Final Project (paper or online project): 70 percent
Project presentation: 10 percent
Final mark for the course is established by determining the weighted average.
Resit
Students who have scored an overall insufficient grade for the course may take a resit for the assignments and the Paper (or online project):
comprehensive take-home exam: (50 percent of grade)
Paper (or online project): (50 percent of grade)
Final mark for the course is established by determining the weighted average.
Exam review
How and when an exam review will take place will be disclosed together with the publication of the exam results at the latest. If a student requests a review within 30 days after publication of the exam results, an exam review will have to be organized.
Reading list
The up-to-date syllabus, which includes all of the readings for the course, will be posted on the Brightspace
Registration
Enrolment through uSis is mandatory.
General information about uSis is available in English and Dutch
Registration Studeren à la carte and Contractonderwijs
Registration Studeren à la carte and Contractonderwijs