L3: Lexik empirisch und digital
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Recent typological studies have shown that socio-linguistic factors have a substantial effect on at least certain structures of language. However, we are still far from understanding how such factors should be operationalized and how they interact with other factors in shaping grammar. To address both questions, this study examines the influence of socio-linguistic factors on the number of dedicated conditional constructions in a sample of 374 languages. We test the number of speakers, the degree of multilingualism, the availability of a literature tradition, the use of writing, and the use of the language in the education system. At the same time, we control for genealogical, contact, and bibliographical biases. Our results suggest that the number of speakers is the most informative predictor. However, we find that the association between the number of speakers and the number of dedicated conditional constructions is much weaker than assumed, once genealogical and contact biases are controlled for.
In this article, we provide an insight into the development and application of a corpus-lexicographic tool for finding neologisms that are not yet listed in German dictionaries. As a starting point, we used the words listed in a glossary of German neologisms surrounding the COVID-19 pandemic. These words are lemma candidates for a new dictionary on COVID-19 discourse in German. They also provided the database used to develop and test the NeoRate tool. We report on the lexicographic work in our dictionary project, the design and functionalities of NeoRate, and describe the first test results with the tool, in particular with regard to previously unregistered words. Finally, we discuss further development of the tool and its possible applications.
In many countries of the world, perspectives on gender equality and racism have changed in recent decades. One result has been more attention being devoted to traces of androcentric and racist language in society. This also affects dictionaries. In lexicography there are discussions about whether or to what extent social asymmetries are inscribed in dictionaries and if this is still acceptable. The issue of the nature of description plays an important role in this discussion. If sexist usages are often found in language use, i.e. in the corpus data on which the dictionary is based, does the dictionary also have to show them? How is this, in turn, compatible with the normative power of dictionaries? Do dictionaries contribute to the perpetuation of gender stereotypes by showcasing them under the banner of descriptive principles? And what roles do lexicographers play in this process? The article deals with these questions on the basis of individual lexicographical examples and current discussions in the lexicographic and public community.
The NottDeuYTSch corpus is a freely available collection of YouTube comments written under German-speaking videos by young people between 2008 and 2018. The article uses the NottDeuYTSch corpus to investigate how YouTube comments can be used to produce learning materials and how corpora of Digitally-Mediated Communication can benefit intermediate learners of German. The article details the effects of authentic communication within YouTube comments on teenage learners, examining how they can influence the psycholinguistic factors of motivation, foreign language anxiety, and willingness to communicate. The article also discusses the benefits and limitations of using authentic corpus material for the development of teaching material.
This paper introduces the Nottinghamer Korpus deutscher YouTube-Sprache (‘The Nottingham German YouTube Language Corpus’ - or NottDeuYTSch corpus). The corpus comprises over 33 million words, taken from roughly 3 million YouTube comments published between 2008 and 2018, written by a young, German-speaking demographic. The NottDeuYTSch corpus provides an authentic and representative linguistic snapshot of young German speakers and offers significant opportunities for in-depth research in several linguistic fields, such as lexis, morphology, syntax, orthography, multilingualism, and conversational and discursive analysis.
We introduce DeReKoGram, a novel frequency dataset containing lemma and part-of-speech (POS) information for 1-, 2-, and 3-grams from the German Reference Corpus. The dataset contains information based on a corpus of 43.2 billion tokens and is divided into 16 parts based on 16 corpus folds. We describe how the dataset was created and structured. By evaluating the distribution over the 16 folds, we show that it is possible to work with a subset of the folds in many use cases (e.g., to save computational resources). In a case study, we investigate the growth of vocabulary (as well as the number of hapax legomena) as an increasing number of folds are included in the analysis. We cross-combine this with the various cleaning stages of the dataset. We also give some guidance in the form of Python, R, and Stata markdown scripts on how to work with the resource.
Computational language models (LMs), most notably exemplified by the widespread success of OpenAI's ChatGPT chatbot, show impressive performance on a wide range of linguistic tasks, thus providing cognitive science and linguistics with a computational working model to empirically study different aspects of human language. Here, we use LMs to test the hypothesis that languages with more speakers tend to be easier to learn. In two experiments, we train several LMs—ranging from very simple n-gram models to state-of-the-art deep neural networks—on written cross-linguistic corpus data covering 1293 different languages and statistically estimate learning difficulty. Using a variety of quantitative methods and machine learning techniques to account for phylogenetic relatedness and geographical proximity of languages, we show that there is robust evidence for a relationship between learning difficulty and speaker population size. However, contrary to expectations derived from previous research, our results suggest that languages with more speakers tend to be harder to learn.
Developments within the field of Second Language Acquisition (SLA) have meant that scholars are increasingly engaging with corpora and corpus-based resources, providing a source of “‘authentic’ language” to learners and educators (Mitchell 2020: 254), and contributing to “state-of-the-art research methodologies” (Deshors and Gries 2023: 164). However, there are areas in which progress can still be made, particularly in the area of metadata, such as information about the speaker and contexts of the language use, as well as increased variety in the text types and genres of corpora used to develop SLA materials (Paquot 2022: 36). This post discusses one such possibility for increasing the variety of text types and providing a rich source of authentic language that can be used to create engaging SLA materials, particularly for young people learning German, namely the use of the NottDeuYTSch corpus (to download the corpus in a variety of formats, see Cotgrove 2018).
Anders als bei Sonntagspredigten haben die katholischen und evangelischen AutorInnen von Kirche in 1live nur 90 Sekunden zur Verfügung, um ihre christliche Botschaft zu vermitteln. Vorliegender Beitrag untersucht, wie die katholischen und evangelischen AutorInnen dies tun. Welche Inhalte erachten sie für relevant? Welche sprachliche Gestaltung wählen sie? Greifen katholische und evangelische AutorInnen zu den gleichen Inhalten und sprachlichen Mitteln oder zeigen sich konfessionelle Präferenzen und Differenzen? Diesen Fragen soll an einem Korpus aus Kirche in 1live-Radiopredigten aus den Jahren 2012 bis 2021 (= 2.755 Texte mit insgesamt 726.570 Token) mit einem quantitativen und qualitativen Methoden-Mix nachgegangen werden. Die Studie wird im Rahmen des DFG-Projekts „Sprache und Konfession 500 Jahre nach der Reformation“ am Germanistischen Institut der Westfälischen Wilhelms-Universität Münster durchgeführt.
The landscape of digital lexical resources is often characterized by dedicated local portals and proprietary interfaces as primary access points for scholars and the interested public. In addition, legal and technical restrictions are potential issues that can make it difficult to efficiently query and use these valuable resources. As part of the research data consortium Text+, solutions for the storage and provision of digital language resources are being developed and provided in the context of the unified cross-domain German research data infrastructure NFDI. The specific topic of accessing lexical resources in a diverse and heterogenous landscape with a variety of participating institutions and established technical solutions is met with the development of the federated search and query framework LexFCS. The LexFCS extends the established CLARIN Federated Content Search that already allows accessing spatially distributed text corpora using a common specification of technical interfaces, data formats, and query languages. This paper describes the current state of development of the LexFCS, gives an insight into its technical details, and provides an outlook on its future development.