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This study examines asymmetries between so-called inherent and contextual categories in relation to the morphological complexity of the nominal and verbal inflectional domain of languages. The observations are traced back to the influence of adult L2 learning in scenarios of intense language contact. A method for a simple comparison of the amount of inherent versus contextual categories is proposed and applied to the German-based creole language Unserdeutsch (Rabaul Creole German) in comparison to its lexifier language. The same procedure will be applied to two further language pairs. The grammatical systems of Unserdeutsch and other contact languages display a noticeable asymmetry regarding their structural complexity. Analysing different kinds of evidence, the explanatory key factor seems to be the role of (adult) L2 acquisition in the history of a language, whereby languages with periods of widespread L2 acquisition tend to lose contextual features. This impression is reinforced by general tendencies in pidgin and creole languages. Beyond that, there seems to be a tendency for inherent categories to be more strongly associated with the verb, while contextual categories seem to be more strongly associated with the noun. This leads to an asymmetry in categorical complexity between the noun phrase and the verb phrase in languages that experienced periods of intense L2 learning.
This paper reports on recent developments within the European Reference Corpus EuReCo, an open initiative that aims at providing and using virtual and dynamically definable comparable corpora based on existing national, reference or other large corpora. Given the well-known shortcomings of other types of multilingual corpora such as parallel/translation corpora (shining-through effects, over-normalization, simplification, etc.) or web-based comparable corpora (covering only web material), EuReCo provides a unique linguistic resource offering new perspectives for fine-grained contrastive research on authentic cross-linguistic data, applications in translation studies and foreign language teaching and learning.
The 12th Web as Corpus workshop (WAC-XII) looks at the past, present, and future of web corpora given the fact that large web corpora are nowadays provided mostly by a few major initiatives and companies, and the diversity of the early years appears to have faded slightly. Also, we acknowledge the fact that alternative sources of data (such as data from Twitter and similar platforms) have emerged, some of them only available to large companies and their affiliates, such as linguistic data from social media and other forms of the deep web. At the same time, gathering interesting and relevant web data (web crawling) is becoming an ever more intricate task as the nature of the data offered on the web changes (for example the death of forums in favour of more closed platforms).
In this article, we examine the current situation of data dissemination and provision for CMC corpora. By that we aim to give a guiding grid for future projects that will improve the transparency and replicability of research results as well as the reusability of the created resources. Based on the FAIR guiding principles for research data management, we evaluate the 20 European CMC corpora listed in the CLARIN CMC Resource family, individuate successful strategies among the existing corpora and establish best practices for future projects. We give an overview of existing approaches to data referencing, dissemination and provision in European CMC corpora, and discuss the methods, formats and strategies used. Furthermore, we discuss the need for community standards and offer recommendations for best practices when creating a new CMC corpus.
In this Paper, we describe a schema and models which have been developed for the representation of corpora of computer-mediated communicatin (CMC corpora) using the representation framework provided by the Text Encoding Initiative (TEI). We characterise CMC discourse as dialogic, sequentially organised interchange between humans and point out that many features of CMC are not adequately handled by current corpus encoding schemas and tools. We formulate desiderata for a representation of CMC in encoding schemes and argue why the TEI is a suitable framework for the encoding of CMC corpora. We propose a model of basic CMC units (utterances, posts, and nonverbal activities) and the macro- and micro-level structures of interactions in CMC environments. Based on these models, we introduce CMC-core, a TEI customisation for the encoding of CMC corpora, which defines CMC-specific encoding features on the four levels of elements, model classes, attribute classes, and modules of the TEI infrastructure. The description of our customisation is illustrated by encoding examples from corpora by researchers of the TEI SIG CMC, representing a variety of CMC genres, i.e. chat, wiki talk, twitter, blog, and Second Life interactions. The material described, i.e. schemata, encoding examples, and documentation, is available from the of the TEI CMC SIG Wiki and will accompany a feature request to the TEI council in late 2019.
We present recognizers for four very different types of speech, thought and writing representation (STWR) for German texts. The implementation is based on deep learning with two different customized contextual embeddings, namely FLAIR embeddings and BERT embeddings. This paper gives an evaluation of our recognizers with a particular focus on the differences in performance we observed between those two embeddings. FLAIR performed best for direct STWR (F1=0.85), BERT for indirect (F1=0.76) and free indirect (F1=0.59) STWR. For reported STWR, the comparison was inconclusive, but BERT gave the best average results and best individual model (F1=0.60). Our best recognizers, our customized language embeddings and most of our test and training data are freely available and can be found via www.redewiedergabe.de or at github.com/redewiedergabe.
Die vorgestellte Studie untersucht die Anteile unterschiedlicher Redewiedergabeformen im Vergleich zwischen zwei Literaturtypen von gegensätzlichen Enden des Spektrums: Hochliteratur – definiert als Werke, die auf der Auswahlliste von Literaturpreisen standen – und Heftromanen, massenproduzierten Erzählwerken, die zumeist über den Zeitschriftenhandel vertrieben werden und früher abwertend als „Romane der Unterschicht” (Nusser 1981) bezeichnet wurden. Unsere These ist, dass sich diese Literaturtypen hinsichtlich ihrer Erzählweise unterscheiden, und sich dies in den verwendeten Wiedergabeformen niederschlägt. Der Fokus der Untersuchung liegt auf der Dichotomie zwischen direkter und nicht-direkter Wiedergabe, die schon in der klassischen Rhetorik aufgemacht wurde.
Individuals with Autism Spectrum Disorder (ASD) experience a variety of symptoms sometimes including atypicalities in language use. The study explored diferences in semantic network organisation of adults with ASD without intellectual impairment. We assessed clusters and switches in verbal fuency tasks (‘animals’, ‘human feature’, ‘verbs’, ‘r-words’) via curve ftting in combination with corpus-driven analysis of semantic relatedness and evaluated socio-emotional and motor action related content. Compared to participants without ASD (n=39), participants with ASD (n=32) tended to produce smaller clusters, longer switches, and fewer words in semantic conditions (no p values survived Bonferroni-correction), whereas relatedness and content were similar. In ASD, semantic networks underlying cluster formation appeared comparably small without afecting strength of associations or content.