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(in Vorbereitung) Shrines of Wisdom - Learning, Knowledge, and the Architecture of Libraries

Heinrich, Michael (2025)

Buchpublikation, Mitherausgabe und Buchkapitel, Transcript Verlag.


Peer Reviewed

(in Vorbereitung) Handbuch für Angewandte Ästhetik

Heinrich, Michael (2025)

Buchpublikation, Transcript Verlag.


Peer Reviewed

(in Vorbereitung) Metadisziplinarität in der Architekturforschung

Heinrich, Michael (2025)

Handbuch der Architekturwissenschaften, Hrsg. K. Berr, A. Hahn & P. Lohmann, Springer Verlag.


Peer Reviewed

(in Vorbereitung) Bedürfnisse als Spannungsfeld: Neue Anwendungsstrukturen der Humanorientierung in Architektur und Design

Heinrich, Michael (2025)

Bedürfnisorientierung in der Innenarchitektur: Ansätze und Methoden aus Forschung und Praxis, Transcript Verlag.


Peer Reviewed

(in Vorbereitung) Die Ästhetik gebauter Lebenswelten und ihre gesellschaftliche Relevanz

Heinrich, Michael (2025)

Für eine nachhaltige Architektur der Stadt, Wagenbach Verlag, 2025.



(in Vorbereitung) Die Ästhetik des Baubestands: Potential für Wohlbefinden und Sinnhaftigkeit

Heinrich, Michael (2025)

Keynote, Bestand transformieren, Räume neu denken! BDIA-Summit 2025, Bund Deutscher Innenarchitekten, Jahreskonferenz, Berlin.



(in Vorbereitung) Schönheit. Subjektive Gewissheit und objektiver Zankapfel

Heinrich, Michael (2025)

Einzelausgabe zur Heftreihe "Die Geschichte hinter dem Bild", Landeszentrale für politische Bildung, Thüringen.



(in Vorbereitung) Ästhetik in der Architektur

Heinrich, Michael (2025)

Keynote, LEADER-Region Tourismusverband Moststraße/ Niederösterreichische Landesausstellung, Niederösterreich.



(in Vorbereitung) Psychological needs, their aesthetic correlates and the formal answers of architecture & art

Heinrich, Michael (2025)

Vortrag, Image Neuroscience and the Arts, Neurocognitive Image Lab, International Studies University, Internationale Fachkonferenz, Shanghai, China.



(in Vorbereitung) Architekturwahrnehmung und metadisziplinäre Ästhetik

Heinrich, Michael (2025)

Kontaktkreis der Münchner Architekturverbände, Bayerische Architektenkammer, München.



MANDALA.ML: A Life Cycle-Centric and Role-Aware Methodology for Agile Machine Learning Projects

Reiche, Michael; Leidner, Jochen L. (2025)

The 24th International Conference on Intelligent Software Methodologies, Tools, and Techniques (SOMET 2025), Kitakyushu, Japan, September 23-26, 2025.


Peer Reviewed
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Large Language Models for the Automated Detection and Classification of Media Bias and Propaganda to foster Media Literacy among News Audiences

Menzner, Tim (2025)

Doctoral Consortium contribution, Proceedings of the Ninth Euopean Conference on Information Literacy (ECIL'25), from 22-25 September 2025, Bamberg, Germany .


Peer Reviewed
 

Media bias is an enduring feature of news dissemination, reflecting the subjective perspectives of its creators across history. From archaic records like "The Victory Stele of Naram-Sin" to contemporary news channels, bias permeates media, influencing political, social, and public health narratives. This research aims to investigate the persistent phenomenon of media bias and the potential of large language models (LLMs)(Kojima et al., 2022) in its detection and classification, in order to deploy publicly available software tools aiming to enhance media literacy among news consumers.

Traditionally, media bias served the interests of ruling powers; even with the rise of modern journalism, objectivity is often compromised by commercial pressures and inherent human biases. (Rodrigo-Ginés et al., 2024). As media landscapes evolve, bias continues to shape public opinion, impacting democratic processes and public health perceptions—evident during the COVID-19 pandemic, where polarized media narratives swayed public health decisions and fueled misinformation. (Recio-Román et al., 2023)

Current research on the effects of labeling media bias or propaganda, whether automatically or with human involvement, highlights the complexity of the issue. Depending on different circumstances, labeling can lead to negative outcomes (such as reinforcing filter bubbles by providing means to avoid news with a different perspective), no change in news consumption behavior at all, or, in some cases, an actual improvement in media literacy as intended (Zavolokina et al., 2024).

This research aims to develop a technical solution for the automatic labeling of biased media content, emphasizing several proposals that we hope will lead to a positive effect on media literacy among those presented with the system’s assessments.

These proposals include using a fine-grained taxonomy of bias types rather than a simple binary left/right labeling, focusing on detailed explanations for each model decision in natural language, marking bias at the sentence level rather than at the article or publication level to provide more insights, fine-tuning autoregressive models like GPT-3.5 or Mistral with high-quality examples instead of using “simple” bidirectional models like BERT(Brown et al., 2020) or non-finetuned models, and focusing on the German language, which has not yet been properly explored for such systems.

Understanding readers' perceptions when exposed to bias-labeled content is another facet of this research. It will explore how bias labeling influences readers' views on credibility and neutrality and whether real-time bias indicators affect news consumption behaviors. As mentioned, practical applications serve as a cornerstone of this research. One aim is to implement bias detection systems in real-world settings, such as search engines and news aggregators, to promote balanced information consumption. The development of user tools, like browser extensions highlighting media bias, intends to address public need for transparent information evaluation.

In essence, this research contributes to media literacy enhancement by demystifying media bias through advanced computational methods. By refining detection mechanisms, classifying bias more effectively, and implementing practical tools, it aims to fortify democratic discourse and public understanding, thereby addressing the pervasive influence of media bias in today’s interconnected world.

 

References

Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., … Amodei, D. (2020). Language Models are Few-Shot Learners. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, & H. Lin (Eds.), Advances in Neural Information Processing Systems (Vol. 33, pp. 1877–1901). Curran.

Kojima, T., Gu, S. S., Reid, M., Matsuo, Y., & Iwasawa, Y. (2022). Large language models are zero-shot reasoners. Advances in Neural Information Processing Systems35, 22199–22213.

Recio-Román, A., Recio-Menéndez, M., & Román-González, M. V. (2023). Influence of Media Information Sources on Vaccine Uptake: The Full and Inconsistent Mediating Role of Vaccine Hesitancy. Computation (Basel). https://doi.org/10.3390/computation11100208

Rodrigo-Ginés, F.-J., Carrillo-de-Albornoz, J., & Plaza, L. (2024). A systematic review on media bias detection: What is media bias, how it is expressed, and how to detect it. Expert Systems with Applications237, 121641.

 

Keywords: Media Bias, Large Language Models, Bias Detection, Natural Language Processing, Journalism, Public Opinion, Taxonomy

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Welcome to the ML Team: A Chat Agent as a Project Management Support Agent

Reiche, Michael; Leidner, Jochen L. (2025)

11th Intelligent Systems Conference 2025 (Intellisys'25), 28-29 August 2025, Amsterdam, The Netherlands.


Peer Reviewed
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Mobilitätsforschung für eine sozial-ökologische Transformation. Theorien, Erkenntnisse und Dynamiken des Verkehrshandelns

Busch-Geertsema, Annika; Lanzendorf, Martin; Müggenburg, Hannah; Wilde, Mathias (2025)

Handbuch Verkehrspolitik.
DOI: 10.1007/978-3-658-04777-1_33-2


Peer Reviewed
 

Der vorliegende Beitrag befasst sich mit neueren Erkenntnissen der Mobilitätsforschung zur Erklärung von Verkehrshandeln. Aus der Perspektive verschiedener Disziplinen wird die Wechselwirkung zwischen Mobilität und sozialen Strukturen analysiert und hinsichtlich ihrer Bedeutung für eine sozial-ökologische Transformation des Mobilitätssystems bewertet. Zunächst wird das Verhältnis von Raumstrukturen und Mobilität geklärt, bevor grundlegende Theorien der Umweltpsychologie vorgestellt werden. Anschließend wird die Bedeutung von Routinen sowie von Umbruchsituationen im Lebenslauf für die Veränderung des Verkehrshandelns diskutiert und das darauf basierende Konzept der Mobilitätsbiografien erläutert. Folgerungen für eine sozial-ökologische Transformation des Mobilitätssystems und die dafür notwendige Mobilitätspolitik schließen den Beitrag ab.

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Attachment Theory in the Digital Age: Exploring the Psychosocial Dimensions of Technology Use

Grosch, Christian (2025)

The Human Side of Service Engineering 182.
DOI: 10.54941/ahfe1006400


Open Access Peer Reviewed
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Ansatz und Teilwert von Pensionsrückstellungen für beitragsorientierte Leistungszusagen ohne garantierte Mindestversorgung

Demmler, Uwe (2025)

Steuerrecht aktuell 2025 (1), 48-53.



Sprachmodelle und Gefahren verbunden mit ihrem ‚white hat‘- und ‚black hat‘-Einsatz im Bereich ITSEC & (Counter)Propaganda

18. Wissenschaftstag der Europäischen Metropolregion Nürnberg, Amberg, Amberger Congress Centrum (ACC), Freitag, 11. Juli 2025.


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Learner Models: Design, Components, Structure, and Modelling - A Systematic Literature Review

Böck, Felix; Ochs, Michaela; Henrich, Andreas; Landes, Dieter; Leidner, Jochen L....

User Modeling and User-Adapted Interaction.


Open Access Peer Reviewed
 

Learning is at the heart of every progress the human species makes. It is most effective when it considers who we are as individuals, what learning approach we prefer and what we already know to begin with. In the digital age, we strive to capture such information in the form of a digital representation -- the so-called learner model --, to tailor learning-related systems to this information and build upon it to create more personalised learning experiences. Over recent years, the proliferation of diverse models across various educational applications and disciplines has made it challenging to access targeted research.

In this survey, we aim to address this gap, reviewing the latest advances in learner modelling and conducting a comprehensive analysis of the existing approaches, focusing on developments from 2014 to 2023. With the help of a systematic literature review, we want to provide designers and developers of learner models with a structured overview and simplified entrance into the topic and the field of learner models. We investigate the question: What do learner models look like and how are they filled, kept up-to-date, and used?

To this end, we analyse and classify existing approaches. Our findings provide a comprehensive and structured overview of the field of learner modelling, allowing researchers to navigate and understand the diverse approaches more easily and providing developers of learner models or adaptive systems with a practical tool to access relevant information according to their needs.


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Ästhetik und Bauen: Die Mensch-Umwelt-Beziehung und ihre ästhetische “Benutzeroberfläche“

Heinrich, Michael (2025)

Impulsvortrag, kreativgelöst: Zukunft Bauen. Neue kreative Impulse aus Architektur, Design, Forschung sowie Stadt- und Leerstandsplanung. Thüringen Kreativ/ Thüring. Wirtschaftsministerium.



Entwicklung und Anwendung von Methoden der KI und 5G -Schlussbericht zu AP6

Arbeiter, Georg; Patiño Studencki, Lucila (2025)


Open Access
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Referat Forschungs- und Drittmittelservice (FDS)

Hochschule Coburg

Friedrich-Streib-Str. 2
96450 Coburg


Ansprechperson für Publikationsverzeichnis:

Monika Schnabel
Forschungsreferentin, EU-Referentin
T +49 9561 317 8062
monika.schnabel[at]hs-coburg.de