Open Access

Contents: 1. Andreas Dittrich: Intra-connecting a small exemplary literary corpus with semantic web technologies for exploratory literary studies, S. 1 2. John Kirk, Anna Čermáková: From ICE to ICC: The new International Comparable Corpus, S. 7 3. Dawn Knight, Tess Fitzpatrick, Steve Morris, Jeremy Evas, Paul Rayson, Irena Spasic, Mark Stonelake, Enlli Môn Thomas, Steven Neale, Jennifer Needs, Scott Piao, Mair Rees, Gareth Watkins, Laurence Anthony, Thomas Michael Cobb, Margaret Deuchar, Kevin Donnelly, Michael McCarthy, Kevin Scannell: Creating CorCenCC (Corpws Cenedlaethol Cymraeg Cyfoes – The National Corpus of Contemporary Welsh), S. 13 4. Marc Kupietz, Andreas Witt, Piotr Bański, Dan Tufiş, Dan Cristea, Tamás Váradi: EuReCo - Joining Forces for a European Reference Corpus as a sustainable base for cross-linguistic research, S. 15 5. Harald Lüngen, Marc Kupietz: CMC Corpora in DeReKo, S. 20 6. David McClure, Mark Algee-Hewitt, Douris Steele, Erik Fredner, Hannah Walser: Organizing corpora at the Stanford Literary Lab, S. 25 7. Radoslav Rábara, Pavel Rychlý ,Ondřej Herman: Accelerating corpus search using multiple cores, S. 30 8. John Vidler, Stephen Wattam: Keeping Properties with the Data: CL-MetaHeaders – An Open Specification, S. 35 9. Vladimir Benko: Are Web Corpora Inferior? The Case of Czech and Slovak, S. 43 10. Edyta Jurkiewicz-Rohrbacher, Zrinka Kolaković, Björn Hansen: Web Corpora – the best possible solution for tracking phenomena in underresourced languages: clitics in Bosnian, Croatian and Serbian, S. 49 11. Vít Suchomel: Removing Spam from Web Corpora Through Supervised Learning Using FastText, S. 56

Complex linguistic phenomena, such as Clitic Climbing in Bosnian, Croatian and Serbian, are often described intuitively, only from the perspective of the main tendency. In this paper, we argue that web corpora currently offer the best source of empirical material for studying Clitic Climbing in BCS. They thus allow the most accurate description of this phenomenon, as less frequent constructions can be tracked only in big, well-annotated data sources. We compare the properties of web corpora for BCS with traditional sources and give examples of studies on CC based on web corpora. Furthermore, we discuss problems related to web corpora and suggest some improvements for the future.

We introduce three types of corpora of computer-mediated communication that have recently been compiled at the Institute for the German Language or curated from an external project and included in DeReKo, the German Reference Corpus, namely Wikipedia (discussion) corpora, the Usenet news corpus, and the Dortmund Chat Corpus. The data and corpora have been converted to I5, the TEI customization to represent texts in DeReKo, and are researchable via the web-based IDS corpus research interfaces and in the case of Wikipedia and chat also downloadable from the IDS repository and download server, respectively.

Corpus researchers, along with many other disciplines in science are being put under continual pressure to show accountability and reproducibility in their work. This is unsurprisingly difficult when the researcher is faced with a wide array of methods and tools through which to do their work; simply tracking the operations done can be problematic, especially when toolchains are often configured by the developers, but left largely as a black box to the user. Here we present a scheme for encoding this ‘meta data’ inside the corpus files themselves in a structured data format, along with a proof-of-concept tool to record the operations performed on a file.

This article describes a series of ongoing efforts at the Stanford Literary Lab to manage a large collection of literary corpora (~40 billion words). This work is marked by a tension between two competing requirements – the corpora need to be merged together into higher-order collections that can be analyzed as units; but, at the same time, it’s also necessary to preserve granular access to the original metadata and relational organization of each individual corpus. We describe a set of data management practices that try to accommodate both of these requirements – Apache Spark is used to index data as Parquet tables on an HPC cluster at Stanford. Crucially, the approach distinguishes between what we call “canonical” and “combined” corpora, a variation on the well-established notion of a “virtual corpus” (Kupietz et al., 2014; Jakubíek et al., 2014; van Uytvanck, 2010).