Public event

Data Science Brown Bag Series: Mass Ideology in Germany over Four Decades

Join us for a talk by Sascha Göbel on a comprehensive four-decade analysis reveals fluctuating ideological conflict, contradicting assumptions of consistent depolarization in the German unity.

Abstract from speaker: 

Charting mass ideology is of substantial societal relevance. Knowledge about ideological divides is crucial to understanding the consequences of inequalities in political representation and engagement, serves as a corrective measure in light of misinformed elites, and provides a thermostat for assessing social cohesion. Recent accounts of rising ideological conflict in Europe highlight the importance of assessments of mass ideology. Yet, in Germany, an opposing consensus emerges that portrays the German public as becoming more ideologically united. We review recent literature and point out several limitations that cast doubt on this trend. In response, we offer the first holistic assessment of mass ideology in Germany that spans over four decades of public opinion data, analyzes mass ideology across core issue dimensions at the national and subgroup level, combines different conceptual perspectives, and accounts for measurement error. To achieve this, we implement a hierarchical Bayesian heteroscedastic graded response model that allows for illuminating the topic of mass ideology from different perspectives and poststratify our estimates to German microcensus population counts. Contrary to conventional wisdom, our findings reveal that the German public has not consistently depolarized in the past. Instead, ideological conflict has waxed and waned conditional on the time period, issue dimension, and subgroup at question. In line with current media portrayals, the German public currently shows increasing levels of ideological conflict. We discuss the implication of these findings as regards representational inequalities and social cohesion in Germany as well as for assessments of mass ideology in general.

Bring your own lunch bag! Light pastries and drinks will be available in case you forget to bring it. 

The Data Science Brown Bag Series is an informal and interactive gathering where participants bring their own brown bag lunch and engage in discussions on research and insights the field of data and computational social science (light pastries and drinks will be available if you forget your lunch bag!). 

The series provides a platform for data enthusiasts, researchers, and practitioners to share their experiences, best practices, and emerging methodologies and research in using data science to analyze and understand social and political phenomena. The brown bag talk series is for anyone interested in data science and social science to network, learn, and share ideas in a casual and friendly setting.

 

Contact person

  • William Lowe, Senior Research Scientist
  • Huy Ngoc Dang, Manager of Data Science Lab & Programme Coordinator of Master of Data Science for Public Policy