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pro vyhledávání: '"Hinterreiter, Smi"'
Recent research shows that visualizing linguistic bias mitigates its negative effects. However, reliable automatic detection methods to generate such visualizations require costly, knowledge-intensive training data. To facilitate data collection for
Externí odkaz:
http://arxiv.org/abs/2407.17111
Autor:
Hinterreiter, Smi, Wessel, Martin, Schliski, Fabian, Echizen, Isao, Latoschik, Marc Erich, Spinde, Timo
Media bias is a multifaceted problem, leading to one-sided views and impacting decision-making. A way to address digital media bias is to detect and indicate it automatically through machine-learning methods. However, such detection is limited due to
Externí odkaz:
http://arxiv.org/abs/2407.17045
Autor:
Spinde, Timo, Hinterreiter, Smi, Haak, Fabian, Ruas, Terry, Giese, Helge, Meuschke, Norman, Gipp, Bela
The way the media presents events can significantly affect public perception, which in turn can alter people's beliefs and views. Media bias describes a one-sided or polarizing perspective on a topic. This article summarizes the research on computati
Externí odkaz:
http://arxiv.org/abs/2312.16148
In this study, we are interested in how visual nudges and visualizations can impact and improve the perception of media bias and related concepts. The participants are recruited over Prolific. The Study consists of two parts. In the first part, parti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c4cf70e10013b8d327fd2ed056197a0