Proverbs from a Corpus Linguistic Point of View
Bibliographic Data
| ID | 23665671 |
|---|---|
| Authors | Kathrin Steyer (corresponding author) |
| Year | 2015 |
| Publication date | 2015-04-16 |
| Open Access | No |
| Type | CHAPTER |
| Venue | Introduction to Paremiology (SOURCE_BOOK) |
| Publisher | De Gruyter Open (PUBLISHER • PL) |
| DOI | 10.2478/9783110410167.9 |
| OpenAlex | W2341695838 |
| ISBN | 9783110410167 |
| Language | EN |
| Citations received | 1 |
| References cited | 5 |
This chapter is not a general introduction to corpus linguistics. Instead, I will focus on some aspects which are particularly relevant for the empirical study of proverbs in written language.139 My examples will be based on German written language corpora, specifically the Deutsches Referenzkorpus [German Reference Corpus] (DeReKo) which is located at the Institute for the German Language in Mannheim. The corpus analysis tool used for accessing the corpus data is COSMAS II (CII). However, the questions, search strategies and examples presented in this chapter should be transferable to other corpora and languages. I will discuss how a user who is interested in proverbs can exploit the corpus and which kind of knowledge he can gain in this way. It will become clear that no computer makes thinking obsolete -in the end it is always the human who needs to interpret the results. However, automatic methods can be very useful as they allow high quality pre-structuring of mass data. The most important skill is asking the computer questions as intelligently as possible. Mastering this skill and the methods associated with it is something everyone must learn for themselves by practical experience. As the proverbs say: Grau is alle Theorie [ww: Grey is all theory; ee: An ounce of experience is worth a ton of theory] and bung macht den
Geometry · Linguistics · Point (geometry) · History · Lexicography and Language Studies · Linguistic research and analysis · linguistics and terminology studies · Mathematics · Philosophy
| Citations per year | 0.14 |
|---|---|
| Citation span | 2019 - 2019 (1) |
| Highly cited | No |