ENC2036: Corpus Linguistics
This site is last-updated on 2022-01-05
Annoucements
Important course information will be posted on this web page and announced in class. You are responsible for all material that appears here and should check this page for updates frequently.
- 2022-01-05: The course materials will be updated on a weekly basis. Please note that not all the materials have been complete and make sure that you visit this website regularly to get the most up-to-date materials/information.
- 2022-01-05: For those who are considering taking this course, please read the FAQ first before you make the decision. Please note that there ARE prerequisites for this course.
Course Description
This course aims to introduce theories and practices of Corpus Linguistics as a scientific discipline of its own. Corpus Linguistics has now been considered an interdisciplinary subject, requiring knowledge of linguistic theories, quantitative statistics and data processing. Therefore, this course will provide not only the necessary theoretical foundation but also practical computational skills for students who are interested in conducting corpus-based linguistic research or language-related research. Students are expected to learn:
- the methodological foundations of Corpus Linguistics
- the theoretical bases of Corpus Linguistics
- the technical designs and configuration of standard corpora construction
- the common applications of corpus-linguistic methodology:
- concordances
- frequency lists
- collocations
- keywords
- lexical bundles (n-grams)
- collostructional analyses
- wordclouds
- multi-dimensional vector-space representation of words and texts
- the adequate knowledge for how to make use of existing structured corpora (e.g., BNC, CHILDES, COCA, Sinica Corpus, NCCU Spoken Corpus, ICNALE)
This course is extremely hands-on and will lead the students through classic examples of these corpus-based applications via in-class theme-based tutorial sessions. Unlike most of the corpus linguistic courses offered in other universities, we do not introduce you to ready-made applications or software packages (e.g., Wordsmith, AntConc, Sketch Engine, LancBox, etc.). We hope to point you to the power of coding in computational text analytics. By the end of this course, students should be expected to have achieved the necessary computational proficiency and be able to perform comparable corpus-based analyses on their own data or research questions. In particular, the weekly tutorials will stress the issues of computational text analytics (e.g., web crawling, regular expression, tokenization, segmentation, concordances, collocations, keyword analysis) and statistical processing (e.g., parametric statistical analyses) via hands-on implementation with the language . This course will be a prerequisite for more advanced courses such as ENC2045 Computational Linguistics and ENC2056 Topics on Quantitative Corpus Linguistics.
Course Schedule
(The schedule is tentative and subject to change. Please pay attention to the announcements made during the class.)
| Week | Date | Topic |
|---|---|---|
| Week 1 | 2022-02-18 | Quantitative Corpus Linguistics: A Primer |
| Week 2 | 2022-02-25 | R Fundamentals |
| Week 3 | 2022-03-04 | Data Collection and Corpus Creation: HTML and Web Crawler |
| Week 4 | 2022-03-11 | Concordances, Frequency Lists, N-grams, Collocations |
| Week 5 | 2022-03-18 | Tokenization and Parts-of-speech Tagging |
| Week 6 | 2022-03-25 | Data Retrieval and Coding: Regular Expressions |
| Week 7 | 2022-04-01 | Keywords Analysis |
| Week 8 | 2022-04-08 | Midterm |
| Week 9 | 2022-04-15 | Chinese Text Analytics + Chinese Word Segmentation |
| Week 10 | 2022-04-22 | Constructions and Idioms |
| Week 11 | 2022-04-29 | Structured Corpora Processing |
| Week 12 | 2022-05-06 | XML |
| Week 13 | 2022-05-13 | Near-Synonyms and Distcintive Collexemes |
| Week 14 | 2022-05-20 | Vector-space Representation |
| Week 15 | 2022-05-27 | Final Exam |
| Week 16 | 2022-06-03 | Holiday |
Course Requirement
Course Materials
All the course materials are available on the course website. Please consult the instructor for the direct link to the course materials. They will be provided as a series of online packets (i.e., handouts, script source codes etc.) on the course website. These teaching materials are based on the following recommended readings.
- Stefanowitsch, A. (2019). Corpus Linguistics: A Guide to the Methodology. (In Press)
- Gries, Stefan T. (2017) Quantitative Corpus Linguistics with R: A Practical Introduction. Second Edition. Routledge.
- Winter, Bodo. (2019). Statistics for Linguists: An Introduction Using R. NY:Routledge.
- Desagulier, Guillaume. (2018). Corpus Linguistics and Statistics with R. Cham, Switzerland: Springer.
- Brezina, Vaclav. (2018). Statistics in Corpus Linguistics: A Practical Guide. Cambridge: Cambridge University Press.
Course Website
Email Address
You can reach me at alvinchen@ntnu.edu.tw.
Office Hours
By appointment.
Questions?
If you have any further questions related to the course, please consult FAQ on our course website or write me at any time at alvinchen@ntnu.edu.tw.
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