400013 SE Advanced quantitative text analysis (2023W)

Facing the massive volumes of text data that are available in digital format and valuing their potential, over recent years social scientists have increasingly turned to methods that rely on the support of computer power, so- called computer-assisted or automated text analysis methods. The text-as-data methods are used to draw reproducible and valid inferences or meanings from documents. As an enhancement of the more classical manual methods of content analysis, automated methods of text analysis are becoming prevalent in disciplines that are overall increasingly computationally oriented.
The course covers topics related to data collection, data processing, quality control, and the critical interpretation of results.
We cover the following topics:
What kind of questions can be answered with automated text analysis
Scraping and Using APIs
Pre-processing
Regular Expressions and Classification with dictionaries
Machine Learning and Classification
Topic modeling/k-means
Transformers
Text analysis and network analysis
Multilingual text analysis
Validation
Ethics and Data Security
Critical reflection on the methods

All topics are introduced with a lecture type approach and then illustrated with practical examples. The practical part consists of guided coding sessions, where we work together through prepared code, and of small coding challenges, which are worked on alone or in groups.
We will work mainly with R and Python. To follow the course you should have the following skills: create and manipulate vectors, data frames, and list objects; load tabular data files (e.g., CSVs); perform simple operations (subsetting/filtering, indexing, creating/changing columns) on data frames. If you have not worked with R and Python before, please contact the lectures before taking the course. They will send you a link collection for learning materials that will allow you to acquire the required skills.
This course is aimed at people with some knowledge of automated text analysis who want to use this method in their PhD and/or want to deepen their expertise of the matter.

Please note: The prerequisite for participation in advanced seminars is the conclusion of the doctoral thesis agreement.

Bitte beachten Sie: Voraussetzung für den Besuch von Vertiefungsseminaren ist der Abschluss der Dissertationsvereinbarung.