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Category: Project

Description: We analyze whether the Islamist terror attack on the Christmas market in Berlin in 2016 had an impact on public opinion toward immigration in general and, since the attacker has entered Germany to apply for asylum, toward refugees in particular. An analysis of this natural experiment reveals a negative shift regarding the latter, while no differences are observed for the former. To shed more light on the driver of attitude change, we combine these findings with a quantitative content analysis of online media reporting about refugees before and after the attack. Mass media have long been considered to have an impact on exclusionary attitudes toward ethnic minorities. However, empirical evidence on this relationship remains largely anecdotal. We draw upon unsupervised machine learning to quantify the developments in reporting in three popular German online news websites. Results reveal that the attack had significant impact on media reporting on these websites. However, the strong focus on the attack was only short lived, quickly decreasing already in the second week after the attack. Linking media data to the public opinion data reveals no clear connection between reporting and attitudes. In contrast to theoretical expectations, descriptive evidence even shows that both follow almost opposite trends, since people changed their attitudes only weeks after the attack. We discuss potential explanations of these, at first sight, counterintuitive findings.