Open Access

Der Beitrag stellt die wissenschaftlichen und methodologischen Herausforderungen für die Erstellung einer innovativen, korpusbasierten lexikografischen Ressource zur Lexik des gesprochenen Deutsch in der Interaktion vor und zeigt neue Wege für lexikografische Arbeiten auf. Neben allgemeinen Projektinformationen zu den Ausgangspunkten, der Datengrundlage, den Methoden, Zielen und dem konkreten Gegenstandsbereich werden ausgewählte Ergebnisse von zwei projektbezogenen empirischen Studien zu Erwartungshaltungen an eine lexikografische Ressource des gesprochenen Deutsch präsentiert. Für korpusbasierte quantitative Informationen werden die Möglichkeiten eines Tools, welches im Rahmen des Projekts entwickelt wurde, aufgezeigt. Außerdem wird ein Einblick in die konzeptionellen und methodologischen Überlegungen zur Mikrostruktur der geplanten Ressource gegeben.

We present web services implementing a workflow for transcripts of spoken language following TEI guidelines, in particular ISO 24624:2016 "Language resource management - Transcription of spoken language". The web services are available at our website and will be available via the CLARIN infrastructure, including the Virtual Language Observatory and WebLicht.

Construction-based language models assume that grammar is meaningful and learnable from experience. Focusing on five of the most elementary argument structure constructions of English, a large-scale corpus study of child-directed speech (CDS) investigates exactly which meanings/functions are associated with these patterns in CDS, and whether they are indeed specially indicated to children by their caretakers (as suggested by previous research, cf. Goldberg, Casenhiser and Sethuraman 2004). Collostructional analysis (Stefanowitsch and Gries 2003) is employed to uncover significantly attracted verb-construction combinations, and attracted pairs are classified semantically in order to systematise the attested usage patterns of the target constructions. The results indicate that the structure of the input may aid learners in making the right generalisations about constructional usage patterns, but such scaffolding is not strictly necessary for construction learning: not all argument structure constructions are coherently semanticised to the same extent (in the sense that they designate a single schematic event type of the kind envisioned in Goldberg’s [1995] ‘scene encoding hypothesis’), and they also differ in the extent to which individual semantic subtypes predominate in learners’ input

Transdisciplinary research is research not only on, but also for and, most of all, with practitioners. In the research framework of transdisciplinarity, scholars and practitioners collaborate throughout research projects with the aim of mutual learning. This paper shows the value transdisciplinarity can add to media linguistics. It does so by investigating the digital literacy shift in journalism: the change, in the last two decades, from the predominance of a writing mode that we have termed focused writing to a mode we have called writing-by-the-way. Large corpora of writing process data have been generated and analyzed with the multimethod approach of progression analysis in order to combine analytical depth with breadth. On the object level of doing writing in journalism, results show that the general trend towards writing-by-the-way opens up new niches for focused writing. On a meta level of doing research, findings explain under what conditions transdisciplinarity allows for deeper insights into the medialinguistic object of investigation.

A large database is a desirable basis for multimodal analysis. The devel­opment of more elaborate methods, data banks, and tools for a stronger empirical grounding of multimodal analysis is a prevailing topic within multimodality. Prereq- uisite for this are corpora for multimodal data. Our contribution aims at developing a proposal for gathering and building multimodal corpora of audio-visual social media data, predominantly YouTube data.Our contribution has two parts: First we outline a participation framework which is able to represent the complexity of YouTube communication. To this end we ‘dissect’ the different communicative and multimodal layers YouTube consists of. Besides the Video performance YouTube also integrates comments, social media operators, commercials, and announcements for further YouTube Videos. The data consists of various media and modes and is interactively engaged in various discourses. Hence, it is rather difficult to decide what can be considered as a basic communicative unit (or a ‘turn’) and how it can be mapped. Another decision to be made is which elements are of higher priority than others, thus have to be integrated in an adequate transcription format. We illustrate our conceptual considerations on the example of so-called L e t’s Plays, which are supposed to present and comment Computer gaming processes.The second part is devoted to corpus building. Most previous studies either worked with ad hoc data samples or outlined data mining and data sampling strategies. Our main aim is to delineate in a systematic way and based on the conceptual outline in the first part necessary elements which should be part of a YouTube corpus. To this end we describe in a first Step which components (e.g., the Video itself, the comments, the metadata, etc.) should be captured. ln a second Step we outline why and which relations (e.g., screen appearances, hypertextual struc- tures, etc.) are worth to get part of the corpus. In sum, our contribution aims at outlining a proposal for gathering and systematizing multimodal data, specifically audio-visual social media data, in a corpus derived from a conceptual modeling of important communicative processes of the research object itself.

Language attitudes matter; they influence people’s behaviour and decisions. Therefore, it is crucial to learn more about patterns in the way that languages are evaluated. One means of doing so is using a quantitative approach with data representative of a whole population, so that results mirror dispositions at a societal level. This kind of approach is adopted here, with a focus on the situation in Germany. The article consists of two parts. First, I will present some results of a new representative survey on language attitudes in Germany (the Germany Survey 2017). Second, I will show how language attitudes penetrate even seemingly objective data collection processes by examining the German Microcensus. In 2017, for the first time in eighty years, the German Microcensus included a question on language use ‘at home’. Unfortunately, however, the question was clearly tainted by language attitudes instead of being objective. As a result, the Microcensus significantly misrepresents the linguistic reality of different migrant languages spoken in Germany.