Issues of corpus comparability and register variation in the International Corpus of English: Theories and computer applications





Faculty/Professorship: English and Historical Linguistics  ; Fakultät Geistes- und Kulturwissenschaften: Abschlussarbeiten 
Author(s): Vetter, Fabian  
Publisher Information: Bamberg : Otto-Friedrich-Universität
Year of publication: 2021
Pages: xi, 132 ; Illustrationen, Diagramme + 1 Computer program ICEtree (ZIP-file)
Supervisor(s): Krug, Manfred  ; Schützler, Ole 
Language(s): English
Remark: 
Dissertation, Otto-Friedrich-Universität Bamberg, 2020
DOI: 10.20378/irb-52406
Licence: Creative Commons - CC BY - Attribution 4.0 International 
URN: urn:nbn:de:bvb:473-irb-524063
Abstract: 
This study offers an account of the issue of corpus comparability of components of the International Corpus of English (ICE). By employing quantitative and qualitative methods, it contributes to corpus-based studies of varieties of English, and corpus linguistics as a linguistic discipline more generally. Specifically, it (i) exemplifies how discrepancies in sampling strategies can decrease the comparability of components of comparable corpus families such as ICE, (ii) presents methods to detect such discrepancies, (iii) develops and releases a user-friendly computer program (ICEtree) that allows the application of these methods to components of ICE that are not investigated in this study and (iv) illustrates how a register-based annotation framework could help mitigate some of the conflicting priorities in the use and compilation of comparable corpora.
GND Keywords: The international corpus of English; Korpus <Linguistik>; Vergleich; Englisch; Sprachvariante
Keywords: corpus linguistics, comparability, meta data, register variation, sampling, text clustering, parts-of-speech, linguistic tagging, situational characteristics
DDC Classification: 400 Language & linguistics  
420 English  
RVK Classification: HF 450   
Type: Doctoralthesis
URI: https://fis.uni-bamberg.de/handle/uniba/52406
Release Date: 23. December 2021

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fisba52406_A3a.pdf7.33 MBPDFView/Open
ICEtreeStandaloneVersion1.0.zip301.54 MBUnknownView/Open