A data-driven method to identify (correlated) changes in chronological corpora
- In this paper, an exploratory data-driven method is presented that extracts word-types from diachronic corpora that have undergone the most pronounced change in frequency of occurrence in a given period of time. Combined with statistical methods from time series analysis, the method is able to find meaningful patterns and relationships in diachronic corpora, an idea that is still uncommon in linguistics. This indicates that the approach can facilitate an improved understanding of diachronic processes.
Author: | Alexander KoplenigORCiDGND |
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DOI: | https://doi.org/10.1080/09296174.2017.1311447 |
ISSN: | 0929-6174 (Print) |
ISSN: | 1744-5035 (Online) |
Parent Title (English): | Journal of Quantitative Linguistics |
Publisher: | Routledge, Taylor & Francis |
Place of publication: | London u.a. |
Document Type: | Article |
Language: | English |
Year of first Publication: | 2017 |
Date of Publication (online): | 2017/04/26 |
Reviewstate: | Peer-Review |
Tag: | BNC; COHA; Google Books Ngram corpora; diachronic corpora; text mining; time series analysis |
GND Keyword: | Englisch; Korpus <Linguistik>; Sprachgeschichte; Sprachstatistik; Text Mining; Wortschatz |
Volume: | 24 |
Issue: | 4 |
First Page: | 289 |
Last Page: | 318 |
Note: | Dieser Beitrag ist aus urheberrechtlichen Gründen nicht frei zugänglich. Due to copyright reasons the full-text of the article is not freely accessible. Preprint: http://nbn-resolving.de/urn:nbn:de:bsz:mh39-42569 |
DDC classes: | 400 Sprache / 400 Sprache, Linguistik |
Open Access?: | nein |
Program areas: | Lexik |
Licence (German): | Urheberrechtlich geschützt |