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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.
Song lyrics can be considered as a text genre that has features of both written and spoken discourse, and potentially provides extensive linguistic and cultural information to scientists from various disciplines. However, pop songs play a rather subordinate role in empirical language research so far - most likely due to the absence of scientifically valid and sustainable resources. The present paper introduces a multiply annotated corpus of German lyrics as a publicly available basis for multidisciplinary research. The resource contains three types of data for the investigation and evaluation of quite distinct phenomena: TEI-compliant song lyrics as primary data, linguistically and literary motivated annotations, and extralinguistic metadata. It promotes empirically/statistically grounded analyses of genre-specific features, systemic-structural correlations and tendencies in the texts of contemporary pop music. The corpus has been stratified into thematic and author-specific archives; the paper presents some basic descriptive statistics, as well as the public online frontend with its built-in evaluation forms and live visualisations.
This report presents a corpus of articulations recorded with Schlieren photography, a recording technique to visualize aeroflow dynamics for two purposes. First, as a means to investigate aerodynamic processes during speech production without any obstruction of the lips and the nose. Second, to provide material for lecturers of phonetics to illustrates these aerodynamic processes. Speech production was recorded with 10 kHz frame rate for statistical video analyses. Downsampled videos (500 Hz) were uplodad to a youtube channel for illustrative purposes. Preliminary analyses demonstrate potential in applying Schlieren photography in research.
In this paper, we will present a first attempt to classify commonly confused words in German by consulting their communicative functions in corpora. Although the use of so-called paronyms causes frequent uncertainties due to similarities in spelling, sound and semantics, up until now the phenomenon has attracted little attention either from the perspective of corpus linguistics or from cognitive linguistics. Existing investigations rely on structuralist models, which do not account for empirical evidence. Still, they have developed an elaborate model based on formal criteria, primarily on word formation (cf. Lăzărescu 1999). Looking from a corpus perspective, such classifications are incompatible with language in use and cognitive elements of misuse.
This article sketches first lexicological insights into a classification model as derived from semantic analyses of written communication. Firstly, a brief description of the project will be provided. Secondly, corpus-assisted paronym detection will be focused. Thirdly, in the main section the paper concerns the description of the datasets for paronym classification and the classification procedures. As a work in progress, new insights will continually be extended once spoken and CMC data are added to the investigations.
This paper presents a short insight into a new project at the "Institute for the German Language” (IDS) (Mannheim). It gives an insight into some basic ideas for a corpus-based dictionary of spoken German, which will be developed and compiled by the new project "The Lexicon of spoken German” (Lexik des gesprochenen Deutsch, LeGeDe). The work is based on the "Research and Teaching Corpus of Spoken German” (Forschungs- und Lehrkorpus Gesprochenes Deutsch, FOLK), which is implemented in the "Database for Spoken German” (Datenbank für Gesprochenes Deutsch, DGD). Both resources, the database and the corpus, have been developed at the IDS.
This paper presents the prototype of a lexicographic resource for spoken German in interaction, which was conceived within the framework of the LeGeDe-project (LeGeDe=Lexik des gesprochenen Deutsch). First of all, it summarizes the theoretical and methodological approaches that were used for the initial planning of the resource. The headword candidates were selected by analyzing corpus-based data. Therefore, the data of two corpora (written and spoken German) were compared with quantitative methods. The information that was gathered on the selected headword candidates can be assigned to two different sections: meanings and functions in interaction.
Additionally, two studies on the expectations of future users towards the resource were carried out. The results of these two studies were also taken into account in the development of the prototype. Focusing on the presentation of the resource’s content, the paper shows both the different lexicographical information in selected dictionary entries, and the information offered by the provided hyperlinks and external texts. As a conclusion, it summarizes the most important innovative aspects that were specifically developed for the implementation of such a resource.
In this paper, an exploratory data-driven method is presented that extracts word-types from diachronic corpora that have undergone the most pronounced change in frequency of occurrence in a given period of time. Combined with statistical methods from time series analysis, the method is able to find meaningful patterns and relationships in diachronic corpora, an idea that is still uncommon in linguistics. This indicates that the approach can facilitate an improved understanding of diachronic processes.
In this paper, a method for measuring synchronic corpus (dis-)similarity put forward by Kilgarriff (2001) is adapted and extended to identify trends and correlated changes in diachronic text data, using the Corpus of Historical American English (Davies 2010a) and the Google Ngram Corpora (Michel et al. 2010a). This paper shows that this fully data-driven method, which extracts word types that have undergone the most pronounced change in frequency in a given period of time, is computationally very cheap and that it allows interpretations of diachronic trends that are both intuitively plausible and motivated from the perspective of information theory. Furthermore, it demonstrates that the method is able to identify correlated linguistic changes and diachronic shifts that can be linked to historical events. Finally, it can help to improve diachronic POS tagging and complement existing NLP approaches. This indicates that the approach can facilitate an improved understanding of diachronic processes in language change.