We are pleased to welcome Arianna Haviv-Zehner for an talk presenting her latest research on media discourse and its role in shaping public debates.
Mass media is often investigated for its influence on public opinion. However, media analysis often relies on measuring term prevalence, elements of framing, and determining bias. In this talk, Arianna Haviv-Zehner presents new approaches to media analysis that are advantageous to the social sciences.
Leveraging the German General Social Survey (GGSS), she utilizes Latent Semantic Analysis (LSA) to categorize and compare discourse for key points in time (2006, 2010, 2012, 2016, 2021), drawing on over 10,000 media articles from several German media outlets. The focus lies on migration and the integration of foreigners in Germany, as well as the competing discourse narratives surrounding these developments.
The study adapts the term “foreigner” (Ausländer) in media texts; German compound variations such as Ausländerproblem (foreigner problem) and Ausländerintegration (foreigner integration) are central to the discourse analysis. Based on semantic meaning and co-occurrence, these compound terms are grouped into four categories: Administration and Policy, Social Integration, Xenophobia, and Limiting Migration.
Results demonstrate that Social Integration discourse becomes more prevalent over time. A subsequent sentiment analysis reveals that Social Integration discourse is not positive but neutral, while other categories reflect a negative bias. The talk will further address computational applications for the enhancement of media analysis, as well as challenges to contextualizing survey data.
