arXiv subjects

Sebastian Haunss

Publications and source records attributed to Sebastian Haunss.

4 recordsLinked to original sources

arXiv2026

Comparing and Modeling Argumentation in German Political Communication across Arenas

Deliberation, involving the formulation and exchange of arguments, forms an integral part of political decision making in democracies. Argumentation patterns however differ substantially across different political arenas, such as plenary speeches and committee meetings. However, despite a lot of interest in argumentation, there is comparatively little computational work on analyzing differences in patterns of political argumentation between arenas. Our work addresses this research gap. First, we present a 17k-sentence corpus with annotation for argumentative passages (argument and their justifications, both their boundaries and their categories) across three German political arenas (plenary speeches, committee meetings, and press conferences), keeping the topic (COVID-19) constant. Our analysis of the corpus finds that contrary to expectations, justification by domain-specific expertise is more frequent in press conferences than in committee meetings. Second, we present a pilot study on automatically identifying such argumentative passages. The results show that boundaries are hard to pin down, and models predictions additionally suffer from confirmation bias.

cs.CL↗

arXiv2026

Take the Power Back: Screen-Based Personal Moderation Against Hate Speech on Instagram

Hate speech remains a pressing challenge on social media, where platform moderation often fails to protect targeted users. Personal moderation tools that let users decide how content is filtered can address some of these shortcomings. However, it remains an open question on which screens (e.g., the comments, the reels tab, or the home feed) users want personal moderation and which features they value most. To address these gaps, we conducted a three-wave Delphi study with 40 activists who experienced hate speech. We combined quantitative ratings and rankings with open questions about required features. Participants prioritized personal moderation for conversational and algorithmically curated screens. They valued features allowing for reversibility and oversight across screens, while input-based, content-type specific, and highly automated features are more screen specific. We discuss the importance of personal moderation and offer user-centered design recommendations for personal moderation on Instagram.

cs.HC↗

arXiv2025

Social Media for Activists: Reimagining Safety, Content Presentation, and Workflows

Social media is central to activists, who use it internally for coordination and externally to reach supporters and the public. To date, the HCI community has not explored activists' perspectives on future social media platforms. In interviews with 14 activists from an environmental and a queer-feminist movement in Germany, we identify activists' needs and feature requests for future social media platforms. The key finding is that on- and offline safety is their main need. Based on this, we make concrete proposals to improve safety measures. Increased control over content presentation and tools to streamline activist workflows are also central to activists. We make concrete design and research recommendations on how social media platforms and the HCI community can contribute to improved safety and content presentation, and how activists themselves can reduce their workload.

cs.HC↗

arXiv2024

Revisiting the Exit from Nuclear Energy in Germany with NLP

Annotation of political discourse is resource-intensive, but recent developments in NLP promise to automate complex annotation tasks. Fine-tuned transformer-based models outperform human annotators in some annotation tasks, but they require large manually annotated training datasets. In our contribution, we explore to which degree a manually annotated dataset can be automatically replicated with today's NLP methods, using unsupervised machine learning and zero- and few-shot learning.

cs.CL↗