Media bias and the intolerance of media outlets and citizens to deal with opposing points of
view pose a threat to the proper functioning of democratic processes. In this respect, we …

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 …

The field of cysec is evolving fast. Security professionals are in need of intelligence on past,
current and—ideally—upcoming threats, because attacks are becoming more advanced and …

News stories circulating online, especially on social media platforms, are nowadays a
primary source of information. Given the nature of social media, news no longer are just …

This study aims to investigate media bias in news articles related to defense and foreign
affairs by applying deep learning models and eXplainable artificial intelligence (XAI) …

In the current era of social media and generative AI, an ability to automatically assess the
credibility of online social media content is of tremendous importance. Credibility …

Document embeddings and similarity measures underpin content-based recommender
systems, whereby a document is commonly represented as a single generic embedding …

Predicting the political bias of news headlines is a challenging task that becomes even more
challenging in a multilingual setting with low-resource languages. To deal with this, we …

Language Models (LMs) have shown remarkable potential in healthcare applications, yet
their widespread adoption faces challenges in achieving consistent performance across …

Media bias detection poses a complex, multifaceted problem traditionally tackled using
single-task models and small in-domain datasets, consequently lacking generalizability. To …