Search

As part of the Summer Institute in Computational Social Science (SICSS), the research group engages in international social science methods training and continuing education for advanced MA students, doctoral candidates and postdocs. SICSS-Berlin focuses on digital texts, including data collection through web scraping, data cleaning, as well as various quantitative text analysis methods and procedures. The teaching program features lectures, group tasks and participant-led group research projects.

SRM Special Issue: Learning Through Failures

In recent years, social scientists have increasingly relied on survey experiments to estimate causal effects. As with any experimental design, survey experiments can fail, deviate from (preregistered) plans, or yield results that researchers did not anticipate. Researchers find themselves in situations with null, unexpected, inconsistent, or inconclusive results and must then decide if these are a product of the theory being tested, the experimental design, or both.