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Courses - Fall 2019
SURV
Survey Methodology Department Site
SURV703
(Perm Req)
Computer-Based Content Analysis I
Credits: 1
Grad Meth: Reg, Aud
Prerequisite: Background knowledge in programming in Python and SQL structures.
Recommended: SURV736.
Investigate the foundations of Natural Language Processing (NLP) as tool for analyzing natural language texts in the social sciences, thus providing an alternative to traditional ways of data generation through surveys. The course introduces general use cases for NLP, provides a guide to standard operations on text as well as their implementation in the Python-based Natural Language Toolkit (NLTK) and introduces the text mining functionalities of the WEKA Machine Learning workbench. The theory part of the course worth one credit can be supplemented by an optional project part worth another credit point.