Hasil untuk "German literature"

R. Pennak

N. Çapar, Masaaki Kotabe

C. Ghisetti, K. Rennings

D. Ben-Amos

proliferation. The German Volkskunde, the Swedish folkminne, and the Indian lok sahitya all imply slightly different meanings that the English term "folklore" cannot syncretize completely.' Similarly, anthropologists and students of literature have projected their own bias into their definitions of folklore. In fact, for each of them folklore became the exotic topic, the green grass on the other side of the fence, to which they were attracted but which, alas, was not in their own domain. Thus, while anthropologists regarded folklore as literature, scholars of literature defined it as culture.2 Folklorists themselves resorted to enumerative,3 intuitive,4 and operational definitions; yet, while all these certainly contributed to the clarification of the nature of folklore, at the same time they circumvented the main issue, namely, the isolation of the unifying thread that joins jokes and myths, gestures and legends, costumes and music into a single category of knowledge. The difficulties experienced in defining folklore are genuine and real. They

Miriam Winkler, Verena Blaschke, Barbara Plank

Indirectness is a common feature of daily communication, yet is underexplored in NLP research for both low-resource as well as high-resource languages. Indirect Question Answering (IQA) aims at classifying the polarity of indirect answers. In this paper, we present two multilingual corpora for IQA of varying quality that both cover English, Standard German and Bavarian, a German dialect without standard orthography: InQA+, a small high-quality evaluation dataset with hand-annotated labels, and GenIQA, a larger training dataset, that contains artificial data generated by GPT-4o-mini. We find that IQA is a pragmatically hard task that comes with various challenges, based on several experiment variations with multilingual transformer models (mBERT, XLM-R and mDeBERTa). We suggest and employ recommendations to tackle these challenges. Our results reveal low performance, even for English, and severe overfitting. We analyse various factors that influence these results, including label ambiguity, label set and dataset size. We find that the IQA performance is poor in high- (English, German) and low-resource languages (Bavarian) and that it is beneficial to have a large amount of training data. Further, GPT-4o-mini does not possess enough pragmatic understanding to generate high-quality IQA data in any of our tested languages.

Jonas Kubesch, Lena Huber, Clemens Havas

Automated Essay Scoring (AES) has been explored for decades with the goal to support teachers by reducing grading workload and mitigating subjective biases. While early systems relied on handcrafted features and statistical models, recent advances in Large Language Models (LLMs) have made it possible to evaluate student writing with unprecedented flexibility. This paper investigates the application of state-of-the-art open-weight LLMs for the grading of Austrian A-level German texts, with a particular focus on rubric-based evaluation. A dataset of 101 anonymised student exams across three text types was processed and evaluated. Four LLMs, DeepSeek-R1 32b, Qwen3 30b, Mixtral 8x7b and LLama3.3 70b, were evaluated with different contexts and prompting strategies. The LLMs were able to reach a maximum of 40.6% agreement with the human rater in the rubric-provided sub-dimensions, and only 32.8% of final grades matched the ones given by a human expert. The results indicate that even though smaller models are able to use standardised rubrics for German essay grading, they are not accurate enough to be used in a real-world grading environment.

Ewa Mazurkiewicz

Matthis Kepser

Der Artikel untersucht das Computerspiel Every day the same dream auf seine Potentiale für einen medienreflexiven Sprach- und Literaturunterricht. Das kostenloses Mini Art Game wurde 2009 von Paolo Pedercini entwickelt und handelt von einem Büroangestellten, dessen Leben sich in einer endlosen Routine aus Arbeit und Monotonie abspielt. Der Spieler oder die Spielerin versucht, aus dieser endlosen Schleife auszubrechen. Dabei kommt es zu irritierenden Unbestimmtheitserfahrungen, die zu einer Interpretation herausfordern. Every day the same dream erweist sich als ideales Beispiel für die Auseinandersetzung mit Computerspielen im Deutschunterricht. Es bietet die Möglichkeit, medien-spezifische Kompetenzen aufzubauen, paratextuelle Formate wie Let ́s Plays zu analysieren, kreative Anschlusskommunikation in Form der gamebasierten Miterzählung zu fördern und Reinszenierungen am Beispiel zweier Kurzfilme aus Österreich und Deutschland zu reflektieren. Schüler/-innen können für eine Interpretation gewinnbringend auf Brechts Theorie und Praxis des epischen Theaters zurückgreifen. Das Spiel regt zur kritischen Betrachtung von gesellschaftlichen Themen an, insbesondere im Zusammenhang mit Arbeit und Identität, und fordert dazu heraus, über Lösungen nachzudenken, die außerhalb des Spiels liegen und politische Fragen aufwerfen.   Abstract (english): This is our life, this is my life too. Linguistic-literacy learning with the digital game "Every day the same dream" The article observes the video game Every day the same dream for its potential for media-reflective language and literature lessons. The free mini-art game was developed by Paolo Pedercini in 2009 and is about an office worker whose life takes place in an endless routine of work and monotony. The player tries to break out of this endless loop. This leads to irritating experiences of indeterminacy that challenge interpretation. Every day the same dream proves to be an ideal example for dealing with computer games in German lessons. It offers the opportunity to build up media-specific skills, analyze paratextual formats such as Let’s Plays, promote creative follow-up communication in the form of game-based co-narration and reflect on adaptions using the example of two short films from Austria and Germany. Students can profitably draw on Brecht’s theory and practice of epic theatre for an interpretation. The game encourages critical reflection on social issues, particularly in connection with work and identity, and challenges the players to think about solutions that lie outside the play and to raise political questions.

Rafał Szubert

The subject of this review article is an edited volume by Nina-Maria Klug and Sina Lautenschläger. From the perspective of semantics and linguistics as a cognitive science, the works collected in this volume contribute to cultural, culturally-related onomasiological considerations within the context of language as a cognitive science. The conceptual domain of love is explored through examples from various areas of language use: in online dating communication, gender-specific advice on flirting and courtship communication, the mourning of parents for their deceased children, the grieving process after the death of a surviving partner, marketing strategies, musical-dramatic imaginings of love from a linguistic perspective, the non-linear structure of language, staged animal love in zoo documentary soaps, children’s books, and in the design of interstate relationships. The authors employ interdisciplinary approaches to illuminate the phenomenon of love from both linguistic and cultural-social science perspectives. The book serves as an inspiration and challenge for the reader, occasionally provoking contradiction and critical voices. Precisely because it does not leave the reader indifferent to the important topics addressed in this thematic volume on love, it is highly recommended for conscious and mature language connoisseurs. It is a valuable contribution to the interdisciplinary dialogue on the cultural and linguistic dimensions of love.

Erich Unglaub

Rainer Maria Rilkes Lyrik aus dem Jahr 1898 ist überschaubar und vergleichsweise wenig geachtet. Im Mittelpunkt des Interesses steht in der Forschung das ‚Florenzer Tagebuch‘, das erst posthum 1942 veröffentlicht worden ist. Als Journal einer Bildungsreise im Frühjahr 1898 nach Florenz und Viareggio hält es Kunstwerke der Renaissance-Stadt, Besuche der großen Sammlungen und berühmten Kirchen fest, enthält aber keine eigene Lyrik. Gedichte entstehen dennoch mit von diesen Veduten ganz abweichenden Motiven und ohne klassische Formen. Sie haben weder die großen Vorbilder der Kunst noch die Welt des alltäglichen Touristen zum Gegenstand, sondern bewegen sich topografisch an einem ‚Dritten Ort‘, der als Peripherie und umgebende Landschaft erkennbar ist, aber auch im Personal der kleinen Leute, der unbedeutenden jungen Mädchen, der abgelegenen Rituale einer volkstümlichen Religion. Aus diesen ‚neuen‘ Kontexten schafft Rilke eine Lyrik und Poetik, die sich von epigonalen Stilen der Italien-Dichtung in Mittel- und Nordeuropa absetzt.

Romina Oji, Jenny Kunz

This paper investigates the optimal use of the multilingual encoder model mDeBERTa for tasks in three Germanic languages -- German, Swedish, and Icelandic -- representing varying levels of presence and likely data quality in mDeBERTas pre-training data. We compare full fine-tuning with the parameter-efficient fine-tuning (PEFT) methods LoRA and Pfeiffer bottleneck adapters, finding that PEFT is more effective for the higher-resource language, German. However, results for Swedish and Icelandic are less consistent. We also observe differences between tasks: While PEFT tends to work better for question answering, full fine-tuning is preferable for named entity recognition. Inspired by previous research on modular approaches that combine task and language adapters, we evaluate the impact of adding PEFT modules trained on unstructured text, finding that this approach is not beneficial.

Anne Sielemann, Lena Loercher, Max-Lion Schumacher et al.

In this paper, we present a synthesis pipeline and dataset for training / testing data in the task of traffic sign recognition that combines the advantages of data-driven and analytical modeling: GAN-based texture generation enables data-driven dirt and wear artifacts, rendering unique and realistic traffic sign surfaces, while the analytical scene modulation achieves physically correct lighting and allows detailed parameterization. In particular, the latter opens up applications in the context of explainable AI (XAI) and robustness tests due to the possibility of evaluating the sensitivity to parameter changes, which we demonstrate with experiments. Our resulting synthetic traffic sign recognition dataset Synset Signset Germany contains a total of 105500 images of 211 different German traffic sign classes, including newly published (2020) and thus comparatively rare traffic signs. In addition to a mask and a segmentation image, we also provide extensive metadata including the stochastically selected environment and imaging effect parameters for each image. We evaluate the degree of realism of Synset Signset Germany on the real-world German Traffic Sign Recognition Benchmark (GTSRB) and in comparison to CATERED, a state-of-the-art synthetic traffic sign recognition dataset.

Kirill Solovev, Chiara Drolsbach, Emma Demirel et al.

Short-form video platforms like TikTok reshape how politicians communicate and have become important tools for electoral campaigning. Yet it remains unclear what kinds of political messages gain traction in these fast-paced, algorithmically curated environments, which are particularly popular among younger audiences. In this study, we use computational content analysis to analyze a comprehensive dataset of N=25,292 TikTok videos posted by German politicians in the run-up to the 2025 German federal election. Our empirical analysis shows that videos expressing negative emotions (e.g., anger, disgust) and outgroup animosity were significantly more likely to generate engagement than those emphasizing positive emotion, relatability, or identity. Furthermore, ideologically extreme parties (on both sides of the political spectrum) were both more likely to post this type of content and more successful in generating engagement than centrist parties. Taken together, these findings suggest that TikTok's platform dynamics systematically reward divisive over unifying political communication, thereby potentially benefiting extreme actors more inclined to capitalize on this logic.

Bianca Steffes, Nils Torben Wiedemann, Alexander Gratz et al.

The automated summarisation of long legal documents can be a great aid for legal experts in their daily work. We automatically create summaries (guiding principles) of German judgments by fine-tuning a decoder-based large language model. We enrich the judgments with information about legal entities before the training. For the evaluation of the created summaries, we define a set of evaluation classes which allows us to measure their language, pertinence, completeness and correctness. Our results show that employing legal entities helps the generative model to find the relevant content, but the quality of the created summaries is not yet sufficient for a use in practice.

Jonathan Brandt, Astrid Bensmann, Richard Hanke-Rauschenbach

Following years of controversial discussions about the risks of market-based redispatch, the German transmission network operators finally installed regional redispatch markets by the end of 2024. Since water electrolysers are eligible market participants, the otherwise downwards redispatched renewable energy can be used for green hydrogen production in compliance with European law. To show how different price levels in regional redispatch markets affect green hydrogen production cost and thus the incentive for electrolyser market participation, we use historic redispatch time series and evaluate various power purchase scenarios. Our results show that low price levels can lead to notable production cost reductions, potentially counteracting uncertainties in redispatch power availability and thus incentivising system-beneficial electrolyser siting. In contrast, the possibility of high price levels can nullify an increase in the competitiveness of German and European green hydrogen through production cost reductions and discourage market participation.

Jens Rupprecht, Leon Fröhling, Claudia Wagner et al.

The use of Large Language Models (LLMs) for simulating human perspectives via persona prompting is gaining traction in computational social science. However, well-curated, empirically grounded persona collections remain scarce, limiting the accuracy and representativeness of such simulations. Here, we introduce the German General Social Survey Personas (GGSS Personas) collection, a comprehensive and representative persona prompt collection built from the German General Social Survey (ALLBUS). The GGSS Personas and their persona prompts are designed to be easily plugged into prompts for all types of LLMs and tasks, steering models to generate responses aligned with the underlying German population. We evaluate GGSS Personas by prompting various LLMs to simulate survey response distributions across diverse topics, demonstrating that GGSS Personas-guided LLMs outperform state-of-the-art classifiers, particularly under data scarcity. Furthermore, we analyze how the representativity and attribute selection within persona prompts affect alignment with population responses. Our findings suggest that GGSS Personas provide a potentially valuable resource for research on LLM-based social simulations that enables more systematic explorations of population-aligned persona prompting in NLP and social science research.

Nico Thurow

This paper exploits the linkage of German administrative social security data (German: Integrierte Erwerbsbiografien) and survey data from the socio-economic panel (Sozio-ökonomisches Panel, SOEP) for the characterization of measurement error in metrics quantifying individual-specific labor earnings in Germany. We find that survey participants' decision whether to consent to linkage is non-random based on observables. In that sense, the studied sample does not constitute a random sample of SOEP. Further, measurement error is not classical and differential: We observe underreporting of income on average, autocorrelation, and non-zero correlation with the true signal and other observable characteristics. In levels, calculated reliability ratios above 0.94 hint at a relatively small attenuation bias in simple linear univariate regressions with earnings as the explanatory variable. For one-period changes in income the bias from measurement error is exacerbated.

Christian Arnold, Daniel Kiel, K. Voigt

The Industrial Internet of Things (IIoT) poses large impacts on business models (BM) of established manufacturing companies within several industries. Thus, this paper aims at analyzing the influence of the IIoT on these BMs with particular respect to differences and similarities dependent on varying industry sectors. For this purpose, we employ an exploratory multiple case study approach based on semi-structured expert interviews in 69 manufacturing companies from the five most important German industries. Owing the lack of previous research, our study contributes to the current state of management literature by revealing the following valuable insights with regard to industry-specific BM changes: The machine and plant engineering companies are mainly facing changing workforce qualifications, the electrical engineering and information and communication technology companies are particularly concerned with the importance of novel key partner networks, and automotive suppliers predominantly exploit IIoT-inherent benefits in terms of an increasing cost efficiency.

G. Hoetker, Thomas Mellewigt

R. Weinrich, M. Strack, Felix Neugebauer

Current meat production places high costs on the environment. However, only a small portion of consumers are willing to opt for meat substitutes or a vegetarian diet. Cultured meat may contribute to solve this dilemma. In this journal, Bryant and Barnett recently reviewed current attitude research and summarized objections perceived by consumers concerning cultured meat. However, no research from Germany was available. Thus, we conducted a survey of German participants, including attitudes previously found to be important in the literature. With a panel sample of 713 consumers, attitudes were found to structure in three dimensions: ethics (e.g., animal welfare, ecological) was the strongest positive driver and depended on pre-knowledge available for 38% of participants; emotional objections (e.g., unnatural) were the second strongest predictor but unrelated to pre-knowledge and demographics; and the third attitudinal dimension expresses concern over the global diffusion of cultured meat. A path model summarizes the results. In conclusion, Germany shows itself to be only moderately prepared to accept cultured meat.