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Instructors: Daniel Baumann
Event type:
Seminar / exercise
Org-unit: Politics, Administration & International Relations
Displayed in timetable as:
Advanced Methods | X | Introduction to computer-based text analysis 1: Basic text analysis with R
Hours per week:
3
Credits:
3,0
Location:
Campus der Zeppelin Universität
Language of instruction:
Englisch
Min. | Max. participants:
5 | 35
Priority scheme: Standard-Priorisierung
Course content:
A key challenge of our time is the analysis of a steadily growing amount of text. Every day, new collections emerge that no human being can assess in a reasonable amount of time: be it newspaper articles, statements, protocols, blog posts, or posts in social media. To facilitate the analysis of large amounts of text, we draw on computer-based methods. In this seminar, students engage with such procedures for quantitative text analysis, methods for the extraction of text-based information, and statistical procedures to analyze huge text corpora.
In the seminar we will use the United Nations Security Council Speeches dataset (Schoenfeld et al. 2019) as the main empirical example. It covers all 82,165 speeches in the UNSC from 1995 to 2020.
Important: This seminar is to be seen in connection with the "Introduction to computer-based text analysis 2: Research Applications" seminar by Professor Eckhard and prepares methodically for it.
Educational objective:
After successful completion of the seminar, students will be familiar with a wide range of methods and applications for working with different types of texts as data and computer-based text analysis and will be able to apply these methods in their own research projects.
Further information about the exams:
Exercises during the sessions and a research proposal for a term paper with computational text analysis on the UNSC speeches dataset or another suitable text dataset. The research proposal can be further pursued in the second part of the seminar offered by Steffen Eckhard.
Mandatory literature:
Grimmer J., & Stewart B. (2013): Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts. Political Analysis, 21(3), 267-297. https://doi.org/10.1093/pan/mps028
https://arxiv.org/abs/1906.10969
DATA: Schönfeld Mirco, Eckhard Steffen, Patz Ronny, Meegdenburg Hilde van, Pires Antonio (2019): The UN Security Council Debates, https://doi.org/10.7910/DVN/KGVSYH, Harvard Dataverse, V5.
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