Abstract Machine learning models learn low-dimensional representations from complex high-
dimensional data. Not only computer science but also social science has benefited from the …

Search engines serve as information gatekeepers on a multitude of topics dealing with
different aspects of society. However, the ways search engines filter and rank information …

Possibilities of applying automated content analysis in journalism studies include, for
example, machine learning to identify topics in journalistic coverage or measuring news …

We present the first comprehensive empirical evaluation of pre-trained language models
(PLMs) for legal natural language processing (NLP) in order to examine their effectiveness …

News coverage plays a crucial role in the formation of attitudes toward ethnic and religious
minority groups. On the attitudinal level, it is an established notion that individuals' explicit …

Why are some diseases more stigmatized than others? And, has disease stigma declined
over time? Answers to these questions have been hampered by a lack of comparable …

In this study, we examine gender differences in political news coverage to determine
whether the media employ stereotypical traits in portrayals of 1,095 US politicians. Using a …

Computational methods have added new approaches to the way many communication
scientists do their work. We identify four developments that accelerated the adaption of …

Themen journalistischer Berichterstattung durch maschinelles Lernen identifizieren oder
Nachrichtendiffusion automatisiert messen: Die Anwendungsmöglichkeiten der …

We propose a new method that embeds speakers into a spatial representation according to
the linguistic similarity of their contributions to a debate. Such “speaker landscapes” can be …