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Wikipedia is a valuable resource, useful as a lingustic corpus or a dataset for many kinds of research. We built corpora from Wikipedia articles and talk pages in the I5 format, a TEI customisation used in the German Reference Corpus (Deutsches Referenzkorpus - DeReKo). Our approach is a two-stage conversion combining parsing using the Sweble parser, and transformation using XSLT stylesheets. The conversion approach is able to successfully generate rich and valid corpora regardless of languages. We also introduce a method to segment user contributions in talk pages into postings.
CLARIAH-DE cross-service search - prospects and benefits of merging subject-specific services
(2021)
CLARIAH-DE combines services and offerings of CLARIN-D and DARIAH-DE. This includes various search applications which are made directly available to researchers. These search applications are presented in this working paper based on their main characteristics and compared with a focus on possible harmonizations. Opportunities and risks of different forms of technical integration are highlighted. Identified challenges can be explained in particular considering the background of different organizational and technical frameworks as well as highly specific and discipline-dependent requirements. The integration work that has already been carried out and the experiences gained with regard to future work and possible integration of further applications are also discussed. The experiences made in CLARIAH-DE can especially be of interest for other projects in the field of digital research infrastructures.
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.