Now You See Me, Now You Don’t: Applying Automated Content Analysis to Track Female Migrants’ Salience in German News

Author(s): Fabienne Lind, Christine Meltzer
Abstract: Reading media headlines and articles about migration, one quickly gets the impression that the media discourse is focussed on migrant men. To investigate to what extend this perception actually holds true, in this study we examine the visibility of gender in media coverage about migrants. We present a validated keyword-based dictionary that allows for automatic and reliable measurement of migrants’ salience (i.e., women, men) in German news coverage. A salience analysis of German migration-related news coverage published between January 2003 and December 2017 is undertaken. We investigate the salience of migrant women in migration news over time, their salience relative to migrant men, as well as across media outlets with different political leanings. We find that migrant women are salient in 12 to 26 per cent of migration-related news articles, whereas migrant men are referred to in almost all migration-related articles. We contextualize these results with actual immigration statistics, discuss the problematic nature of the findings, and weigh the opportunities for and limitations of automatically tracking women migrants in the media against each other.
Organisation(s): Department of Communication
External organisation(s): Johannes Gutenberg-Universität Mainz
Journal: Feminist Media Studies
Volume: 21
Pages: 923-940
No. of pages: 18
ISSN: 1468-0777
DOI: https://doi.org/10.1080/14680777.2020.1713840
Publication date: 2019
Peer reviewed: Yes
Austrian Fields of Science 2012: 508005 Journalism
Keywords
ASJC Scopus subject areas: Communication, Gender Studies, Visual Arts and Performing Arts
Portal url: https://ucris.univie.ac.at/portal/en/publications/now-you-see-me-now-you-dont-applying-automated-content-analysis-to-track-female-migrants-salience-in-german-news(8387df25-d5bf-4681-bc45-d57f9f737f5d).html