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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.

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  • Koplenig_A Data Driven Method to Identify Correlated Changes in Chronological Corpora_2017.pdf
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Metadaten
Author:Alexander KoplenigGND
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 Gr√ľnden nicht frei zug√§nglich.
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
Dewey Decimal Classification:400 Sprache / 400 Sprache, Linguistik
Open Access?:Nein
Licence (German):Es gilt das UrhG