Suchergebnisse

Today's high-choice media environment allows citizens to select news in line with their political preferences and avoid content counter to their priors. So far, however, selective exposure research has exclusively studied news selection based on textual cues, ignoring the recent proliferation of visual media. This study aimed to identify the contribution of visuals alongside text in selective exposure to pro-attitudinal, counter-attitudinal and balanced content. Using two experiments, we created a social media-style newsfeed with news items comprising matching and non-matching images and headlines about the contested issues of immigration and gun control in the U.S. By comparing selection behavior of participants with opposing prior attitudes on these topics, we pulled apart the contribution of images and headlines to selective exposure. Findings show that headlines play a far greater role in guiding selection, with the influence of images being minimal. The additional influence of partisan source cues is also considered.

Abstract
The current study explores how the cultural distance of ethnic outgroups relative to the ethnic ingroup is related to stereotypical news representations. It does so by drawing on a sample of more than three million Dutch newspaper articles and uses advanced methods of automated content analysis, namely word embeddings. The results show that distant ethnic outgroup members (i. e., Moroccans) are associated with negative characteristics and issues, while this is not the case for close ethnic outgroup members (i. e., Belgians). The current study demonstrates the usefulness of word embeddings as a tool to study subtle aspects of ethnic bias in mass-mediated content.