Vorlesungs­verzeichnis

Doing research with text corpora

136038 UE 2025S

Ansicht in u:find »

Moodle

Vortragende der Germanistik:

• Klaus Hofmann

Nächster Termin

Mittwoch, 07.05.2025 09:45-13:00 Hörsaal 5 Hauptgebäude, Tiefparterre Stiege 9 Hof 5

 

Ziele, Inhalte und Methode der Lehrveranstaltung

The course introduces students to the study of text corpora. A corpus, in its broadest sense, is a structured collection of texts. In modern usage, this usually refers to a digital text collection that is annotated with respect to a pre-defined set of analytically relevant features. Although the systematic study of machine-readable text corpora as an empirically based method has mostly been developed within the field of linguistics, text corpora can be useful for investigating all sorts of research questions within the Digital Humanities.
The course will first introduce students to a number of corpora that are available online. Students will learn to apply various browser-based search and analysis tools. Next, students will learn how to compile and annotate their own corpus using tools based in machine-learning. Students will become acquainted with the various formats that different corpora are encoded in, with a particular focus on XML formats. Students will learn how to apply various methods for analysing corpus-derived data, including basic statistical testing, regression modelling, and sentiment analysis. They will also learn how to visualize their results and present their research in the form of a poster or oral presentation.

The software primarily used for corpus construction and analysis is R (including wrappers of Python-based tools). In addition, we will also be discussing corpus analysis software with ready-made usage interfaces like LancsBox X as well as browser-based corpus analysis tools like SketchEngine.

The approach is both theoretical and practical, with hands-on exercises in project planning and prototyping. Students are expected to have some familiarity with digital environments, and previous practice with programming is advantageous, but not strictly mandatory. The course will be mostly held in English, but some code-switching between English and German will invariably occur.

 

Art der Leistungskontrolle und erlaubte Hilfsmittel

Attendance and participation in class
Home exercises and assignments
Oral or poster presentation
Written project portfolio

 

Literatur

Braun, Christian & Elisabeth Scherr (eds.). 2023. Methoden zur Erforschung grammatischer Strukturen in historischen Quellen: Vom Einzelfall zum System. De Gruyter. https://doi.org/10.1515/9783110784282
Gillings, Mathew, Gerlinde Mautner & Paul Baker. 2023. Corpus-assisted discourse studies. Cambridge University Press. https://doi.org/10.1017/9781009168144
Gries, Stefan T. (2021). Statistics for linguistics with R: A practical introduction (Third edition). De Gruyter.
Levshina, Natalia. (2015). How to do linguistics with R. Data exploration and statistical analysis. John Benjamins.
McEnery, Tony & Wilson, Andrew. (2022). Corpus linguistics. Edinburgh University Press.
McDonnell, Duncan & Ondelli, Stefano. (2022). The language of right-wing populist leaders: Not so simple. Perspectives on Politics, 20(3), 828–841. https://doi.org/10.1017/S1537592720002418
Meyer, Charles F. (2023). English corpus linguistics: An introduction (Second edition). Cambridge University Press.
Winter, Bodo. (2019). Statistics for linguists: An introduction using R. Routledge.

 

Prüfungsstoff

There is no exam for the course. In addition to regular reading assigments, the grade will mostly be based on a research project showcasing the skills taught in class.

 

Mindestanforderungen und Beurteilungsmaßstab

Assessment will be based on:
regular attendance and participation (20%)
home exercises and assignments (20%)
oral or poster presentation (30%)
written project portfolio (30%)