Mining corpora of computer-mediated communication: analysis of linguistic features in Wikipedia talk pages using machine learning methods

Machine learning methods offer a great potential to automatically investigate large amounts of data in the humanities. Our contribution to the workshop reports about ongoing work in the BMBF project KobRA (http://www.kobra.tu-dortmund.de) where we apply machine learning methods to the analysis of big corpora in language-focused research of computer-mediated communication (CMC). At the workshop, we will discuss first results from training a Support Vector Machine (SVM) for the classification of selected linguistic features in talk pages of the German Wikipedia corpus in DeReKo provided by the IDS Mannheim. We will investigate different representations of the data to integrate complex syntactic and semantic information for the SVM. The results shall foster both corpus-based research of CMC and the annotation of linguistic features in CMC corpora.

Metadaten
Author:	Michael Beißwenger, Harald Lüngen GND, Eliza Margaretha, Christian Pölitz
URN:	urn:nbn:de:gbv:hil2-opus-2893
Parent Title (English):	Proceedings of the 12th edition of the KONVENS conference Vol. 1
Publisher:	Universität Hildesheim
Place of publication:	Hildesheim
Editor:	Gertrud Faaß, Josef Ruppenhofer
Document Type:	Conference Proceeding
Language:	English
Year of first Publication:	2014
Date of Publication (online):	2014/11/03
Tag:	Data Mining; KorAP (Korpusanalyseplattform der nächsten Generation); Korpuslinguistik; internetbasierte Kommunikation
GND Keyword:	Computerlinguistik; Korpus <Linguistik>; Textkorpus
First Page:	42
Last Page:	47
DDC classes:	400 Sprache / 430 Deutsch
Open Access?:	ja
Leibniz-Classification:	Sprache, Linguistik
Linguistics-Classification:	Korpuslinguistik
Licence (German):	Creative Commons - Namensnennung-Weitergabe unter gleichen Bedingungen 3.0 Deutschland

Open Access