Korpuslinguistik
Refine
Year of publication
Document Type
- Conference Proceeding (12)
- Article (1)
- Part of a Book (1)
Has Fulltext
- yes (14)
Keywords
- Korpus <Linguistik> (13)
- Deutsch (3)
- Deutsches Referenzkorpus (DeReKo) (3)
- Visualisierung (3)
- Language Variation (2)
- Langzeitarchivierung (2)
- Semasiologie (2)
- Sprachvariante (2)
- Sprachwandel (2)
- word embeddings (2)
Publicationstate
- Veröffentlichungsversion (7)
- Postprint (3)
Reviewstate
- Peer-Review (8)
- (Verlags)-Lektorat (2)
Publisher
- European Language Resources Association (ELRA) (4)
- European Language Resources Association (1)
- European language resources association (ELRA) (1)
- Jagiellonian University; Pedagogical University (1)
- Lancaster University (1)
- Leibniz-Institut für Deutsche Sprache (1)
- Leibniz-Institut für Deutsche Sprache (IDS) (1)
- Nisaba (1)
- University of Birmingham (1)
- Universität Zürich (1)
Newspapers became extremely popular in Germany during the 18th and 19th century, and thus increasingly influential for modern German. However, due to the lack of digitized historical newspaper corpora for German, this influence could not be analyzed systematically. In this paper, we introduce the Mannheim Corpus of Digital Newspapers and Magazines, which in its current release comprises 21 newspapers and magazines from the 18th and 19th century. With over 4.1 Mio tokens in about 650 volumes it currently constitutes the largest historical corpus dedicated to newspapers in German. We briefly discuss the prospect of the corpus for analyzing the evolution of news as a genre in its own right and the influence of contextual parameters such as region and register on the language of news. We then focus on one historically influential aspect of newspapers – their role in disseminating foreign words in German. Our preliminary quantitative results indeed indicate that newspapers use foreign words significantly more frequently than other genres, in particular belles lettres.
This paper reports on the latest developments of the European Reference Corpus EuReCo and the German Reference Corpus in relation to three of the most important CMLC topics: interoperability, collaboration on corpus infrastructure building, and legal issues. Concerning interoperability, we present new ways to access DeReKo via KorAP on the API and on the plugin level. In addition we report about advancements in the EuReCo- and ICC-initiatives with the provision of comparable corpora, and about recent problems with license acquisitions and our solution approaches using an indemnification clause and model licenses that include scientific exploitation.
Distributional models of word use constitute an indispensable tool in corpus based lexicological research for discovering paradigmatic relations and syntagmatic patterns (Belica et al. 2010). Recently, word embeddings (Mikolov et al. 2013) have revived the field by allowing to construct and analyze distributional models on very large corpora. This is accomplished by reducing the very high dimensionality of word cooccurrence contexts, the size of the vocabulary, to few dimensions, such as 100-200. However, word use and meaning can vary widely along dimensions such as domain, register, and time, and word embeddings tend to represent only the most prevalent meaning. In this paper we thus construct domain specific word embeddings to allow for systematically analyzing variations in word use. Moreover, we also demonstrate how to reconstruct domain specific co-occurrence contexts from the dense word embeddings.
We present the use of count-based and predictive language models for exploring language use in the German Reference Corpus DeReKo. For collocation analysis along the syntagmatic axis we employ traditional association measures based on co-occurrence counts as well as predictive association measures derived from the output weights of skipgram word embeddings. For inspecting the semantic neighbourhood of words along the paradigmatic axis we visualize the high dimensional word embeddings in two dimensions using t-stochastic neighbourhood embeddings. Together, these visualizations provide a complementary, explorative approach to analysing very large corpora in addition to corpus querying. Moreover, we discuss count-based and predictive models w.r.t. scalability and maintainability in very large corpora.
Language resources are often compiled for the purpose of variational analysis, such as studying differences between genres, registers, and disciplines, regional and diachronic variation, influence of gender, cultural context, etc. Often the sheer number of potentially interesting contrastive pairs can get overwhelming due to the combinatorial explosion of possible combinations. In this paper, we present an approach that combines well understood techniques for visualization heatmaps and word clouds with intuitive paradigms for exploration drill down and side by side comparison to facilitate the analysis of language variation in such highly combinatorial situations. Heatmaps assist in analyzing the overall pattern of variation in a corpus, and word clouds allow for inspecting variation at the level of words.