Methods of corpus linguistics

Teacher(s)

de Marneffe Marie-Catherine;

Language

French

Prerequisites

LFIAL1530 Introduction to Language Science or another course of introduction to linguistics

Learning outcomes

At the end of this learning unit, the student is able to :
1	Build a corpus of language data (oral or written) for a particular purpose of linguistic research;
2	Handle several computer softwares specialized in corpus analysis;
3	Make a quantitative study on a corpus;
4	Make a qualitative study on a corpus.

Content

GENERAL OBJECTIVES :
(1) To be able to lead, completely and autonomously, a linguistic study on corpora;
(2) To acquire a general knowledge on linguistic corpora (in French, but not only), tools and methods.
SPECIFIC OBJECTIVES :
(1) To design a corpus answering a specific research question;
(2) To collect oral and/or written data + metadata;
(3) To "edit" the data (transcription, cleaning, formatting, encoding, etc.);
(4) To tag the data (at several levels of linguistic analysis) using adequate software;
(5) To formulate research questions / hypotheses;
(6) To choose a methodology of analysis;
(7) To exploit / analyze a corpus according to a chosen methology (qualitative and/or quantitative);
(8) To present the results obtained.

Teaching methods

30 hours of lectures + 10 hours of practical work (dedicated to the realization of a personal research based on the methodology see in the lectures).

Evaluation methods

The final grade is the mean of the grades obtained for the following 4 components:

• Attendance and participation to lectures mandatory since lectures are hands-on (10%)
• Submission of a short homework in R consisting data manipulation and vizualization (at mid-term) (15%)
• Oral presentation of the research on the last day of the course (25%)
• Research paper of 13 pages max. (with bibliography, but without appendices) to be submitted at the start of the exam session (50%

For the summer (August/September) exam session, the continued evaluation will still be applicable. Students who failed one of the components will be offered the possibility to retake the component or another one judged equivalent by the professors.

Other information

Generative artificial intelligence (AI) must be used responsibly and in accordance with academic and scientific integrity practices. Given that scientific integrity requires sources to be cited, the use of generative AI must be explicitly stated: the student is required to state (for example in a footnote) whether they used a generative AI (and which one) in writing their answers/term paper, specifying in what capacity the generative AI was used. The student remains responsible for the content of their work, regardless of the sources/references used. Any use of a generative AI for tasks prohibiting its use will be viewed as cheating.

Online resources

Moodle: https://moodle.uclouvain.be/course/view.php?id=2629

Bibliography

• Avanzi, Mathieu, Béguelin, Marie-José, Diémoz, Federica (éds) (2016) Corpus de français parlé et français parlé des corpus (=Corpus 15).
• Baude, Olivier (sous la dir. de). (2006). Corpus oraux, guide des bonnes pratiques. Paris : éditions du CNRS.
• Zufferey, Sandrine (2020). Introduction à la linguistique de corpus. Londres : ISTE éditions

Teaching materials

• L'ensemble des supports sont disponibles sur Moodle.

Faculty or entity

> ELAL