Universität Wien FIND

Return to Vienna for the summer semester of 2022. We are planning to hold courses mainly on site to enable the personal exchange between you, your teachers and fellow students. We have labelled digital and mixed courses in u:find accordingly.

Due to COVID-19, there might be changes at short notice (e.g. individual classes in a digital format). Obtain information about the current status on u:find and check your e-mails regularly.

Please read the information on https://studieren.univie.ac.at/en/info.

136102 VU Text Mining for Non-Computer Scientists on the Example of Discourse Analysis (2021W)

Continuous assessment of course work
MIXED

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Monday 04.10. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
Monday 11.10. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
Monday 18.10. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
Monday 25.10. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
Monday 08.11. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
Monday 15.11. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
Monday 22.11. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
Monday 29.11. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
Monday 06.12. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
Monday 13.12. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
Monday 10.01. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
Monday 17.01. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
Monday 24.01. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
Monday 31.01. 09:45 - 11:15 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5

Information

Aims, contents and method of the course

Students will get introduced to lexicometric analysis. This is closely related to the methods of text mining and can be applied to critical discourse analysis. Students will work on a case study by focusing on text mining tools and some macro analysis rather than interpretation. From the tool perspective, we will have some special emphasis on KNIME, a free and open-source data analytics, reporting, and integration platform. The students learn to apply common methods of text mining with KNIME and apply this kind of method to custom compiled corpora. With a final introduction to Python we want to show that it can be beneficial to learn a scripting language.

Assessment and permitted materials

Active participation
Work on exercise-sheets
Project work on text mining analysis
Peer-review of other participants
Final exam

Minimum requirements and assessment criteria

20% Exercise sheets (Online-Tests)
50% Use case on discourse analysis
10 % Feedback to lecture and tools used
20% Final Test

Grading:
>87,00 % 1
zwischen 75,00 % und 86,99 %: 2
zwischen 63,00 % und 74,99 %: 3
zwischen 50,00 % und 62,99 %: 4
< 50% : 5

Examination topics

- Discourse analysis
- Techniques of text mining
- Analysis and organization of corpora
- Basics of Natural Language Processing
- Databases for storing text
- Tools of visualization of text content
- Understanding control structures in Python programming
- Python Spacy Package

Reading list

- Jäger, Siegfried; Kritische Diskursanalyse - Eine Einführung
- master thesis: http://othes.univie.ac.at/41123/
- DZUDZEK, I., GLASZE, G., MATTISSEK, A., AND SCHIRMEL, H. Verfahren der lexikometrischen analyse von Textkorpora. In Handbuch Diskurs und Raum. Theorien und Methoden für die Humangeographie sowie die sozial- und kulturwissenschaftliche Raum- forschung., vol. 1. Bielefeld: Transcript-Verlag., 2009, pp. 233–260.
- Vincenzo Tursi, Rosaria Silipo; From Words to Wisdom: An Introduction to Text Mining with KNIME (English Edition)

Association in the course directory

EC: DH2
MA: S-DH (Cluster I: Sprache und Literatur)

Last modified: Tu 14.12.2021 13:48