Open Access

This thesis is a corpus linguistic investigation of the language used by young German speakers online, examining lexical, morphological, orthographic, and syntactic features and changes in language use over time. The study analyses the language in the Nottinghamer Korpus deutscher YouTube‐Sprache ("Nottingham corpus of German YouTube language", or NottDeuYTSch corpus), one of the first large corpora of German‐language comments taken from the videosharing website YouTube, and built specifically for this project. The metadatarich corpus comprises c.33 million tokens from more than 3 million comments posted underneath videos uploaded by mainstream German‐language youthorientated YouTube channels from 2008‐2018. The NottDeuYTSch corpus was created to enable corpus linguistic approaches to studying digital German youth language (Jugendsprache), having identified the need for more specialised web corpora (see Barbaresi 2019). The methodology for compiling the corpus is described in detail in the thesis to facilitate future construction of web corpora. The thesis is situated at the intersection of Computer‐Mediated Communication (CMC) and youth language, which have been important areas of sociolinguistic scholarship since the 1980s, and explores what we can learn from a corpus‐driven, longitudinal approach to (online) youth language. To do so, the thesis uses corpus linguistic methods to analyse three main areas: 1. Lexical trends and the morphology of polysemous lexical items. For this purpose, the analysis focuses on geil, one of the most iconic and productive words in youth language, and presents a longitudinal analysis, demonstrating that usage of geil has decreased, and identifies lexical items that have emerged as potential replacements. Additionally, geil is used to analyse innovative morphological productiveness, demonstrating how different senses of geil are used as a base lexeme or affixoid in compounding and derivation. 2. Syntactic developments. The novel grammaticalization of several subordinating conjunctions into both coordinating conjunctions and discourse markers is examined. The investigation is supported by statistical analyses that demonstrate an increase in the use of non‐standard syntax over the timeframe of the corpus and compares the results with other corpora of written language. 3. Orthography and the metacommunicative features of digital writing. This analysis identifies orthographic features and strategies in the corpus, e.g. the repetition of certain emoji, and develops a holistic framework to study metacommunicative functions, such as the communication of illocutionary force, information structure, or the expression of identities. The framework unifies previous research that had focused on individual features, integrating a wide range of metacommunicative strategies within a single, robust system of analysis. By using qualitative and computational analytical frameworks within corpus linguistic methods, the thesis identifies emergent linguistic features in digital youth language in German and sheds further light on lexical and morphosyntactic changes and trends in the language of young people over the period 2008‐2018. The study has also further developed and augmented existing analytical frameworks to widen the scope of their application to orthographic features associated with digital writing.

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).

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.

This study investigates the language used by six German Gangsta rappers to establish and maintain their identity and authenticity as rappers, in songs released between 2015 and 2016. Gangsta rap is a subgenre of Hip-Hop that emphasises ‘the rappers’ street credibility in texts describing tough [urban] neighbourhoods, violence, misogyny, and the achievement of material wealth’ (Bower 379). The culture of Gangsta rap attracts overwhelmingly negative mainstream media coverage (Muggs; Roper) and is often accused of corrupting ‘standard’ language (Krummheuer). The lyrical content of the songs is indeed controversial and has been previously covered by many academics (Byrd; Littlejohn and Putnam; Bower; Rollefson), as has the emergence of Hip-Hop in Germany (Elflein; Pennay; Nitzsche and Grünzweig).

This paper presents an extended annotation and analysis of interpretative reply relations focusing on a comparison of reply relation types and targets between conflictual pages and neutral pages of German Wikipedia (WP) talk pages. We briefly present the different categories identified for interpretative reply relations to analyze the relationship between WP postings as well as linguistic cues for each category. We investigate referencing strategies of WP authors in discussion page postings, illustrated by means of reply relation types and targets taking into account the degree of disagreement displayed on a WP talk page. We provide richly annotated data that can be used for further analyses such as the identification of interactional relations on higher levels, or for training tasks in machine learning algorithms.