Publications

Online abuse in the form of online hostility and hate speech has become an increasing concern in digital publics, particularly affecting individuals engaging in political discourse. While research has extensively examined abuse on text-based platforms, little is known about how this phenomenon manifests on TikTok, a platform characterized by short-form videos, algorithm-driven virality, and participatory affordances. This study investigates the conditions and effects of online abuse on TikTok, focusing on German #PolitTikTok creators, who produce political content. Through, 21 semi-structured interviews, we explore (RQ1) how TikTok shapes online abuse, (RQ2) which factors make creators targets of online abuse, and ...

This report presents an overview of the benefits of implementing variable-level PIDs with regard to the FAIRness of data and offers a practical checklist outlining the requirements for service providers and the challenges faced by infrastructures aiming to adopt variable-level PIDs. In addition, it provides insights into the technical implementation of the PID test environment.

Nacaps, the National Academics Panel Study, is a new longitudinal study of doctoral candidates and doctorate holders in Germany funded by the Federal Ministry of Education and Research (BMBF). The project aims at providing nationwide cross-sectional and longitudinal data on doctoral candidates and doctorate holders in Germany regarding their study conditions as well as their career trajectories within and outside of academia. The Nacaps study series apply a panel design to multiple cohorts. Nacaps 2018 is the first cohort in this series of studies. In 2019, all doctoral candidates registered at 53 higher education institutions entitled to award PhDs/doctorates [...] Full Abstract: https://doi.org/10.21249/DZHW:nac2018:3.0.0

Nacaps, the National Academics Panel Study, is a new longitudinal study of doctoral candidates and doctorate holders in Germany funded by the Federal Ministry of Education and Research (BMBF). The project aims at providing nationwide cross-sectional and longitudinal data on doctoral candidates and doctorate holders in Germany regarding their study conditions as well as their career trajectories within and outside of academia. The Nacaps study series apply a panel design to multiple cohorts. Nacaps 2018 is the first cohort in this series of studies. In 2019, all doctoral candidates registered at 53 higher education institutions entitled to award PhDs/doctorates in Germany [...] Full Abstract: https://doi.org/10.21249/DZHW:nac2018:3.0.0

While Automated Machine Learning (AutoML) systems have shown strong performance on structured data, their application to natural language processing (NLP) tasks remains limited by static, task-agnostic search spaces. In this work, we propose a context-aware extension of AutoPyTorch that dynamically adapts both the hyperparameter search space and neural architecture configuration based on corpus-level meta-features. Our approach extracts interpretable textual statistics—such as average sequence length, vocabulary richness, and class imbalance—to guide the configuration of key hyperparameters. We also introduce two adaptive neural backbones, whose structures are shaped by these meta-features to improve model expressiveness and generalization.

The DZHW Scientists Survey 2023 is an online survey of full-time academic and artistic staff at German universities and equivalent institutions of higher education with the right to award doctorates. It is repeated at regular intervals as a trend study to explore the working and research conditions at German universities and equivalent institutions of higher education. The DZHW Scientists Survey 2023 was conducted from January to March 2023. The respondents therefore take a retrospective look at their working and research conditions during the Covid-19 pandemic and their current post-pandemic situation. The previous Scientists Surveys took place in 2010, 2016 and 2019/2020. [...] Full Abstract: https://doi.org/10.21249/DZHW:scs2023:2.0.0

The Trend Survey Research Data Infrastructures 2024 is part of the accompanying research of the Basic Services for the National Research Data Infrastructure (Base4NFDI). The trend survey captures the perception, use and evaluation of established and new data infrastructures and services in the German research landscape. The focus in on the perspective of (potential) users.