Data Science Unit
With the SNV Data Science Unit, we are expanding our think tank work to include quantitative, data-driven methods. These can provide a broader perspective or deeper insight into a topic and allow us to test assumptions, identify new questions and see connections in data to better understand emerging technologies and shape their impact on society.
We focus on political and social issues of digital technologies and business models: How effective are social network policies in combating disinformation? How error-prone and possibly discriminatory are certain AI systems, or how active are individual interest groups in ongoing international negotiations? For questions like these, we evaluate, for example, patent databases, job platforms, large quantities of text documents, our own surveys or conference papers.
In addition to tapping into new data sources, our work includes network analyses that help us better understand topics and their actors; automated text analyses that allow us to draw on and evaluate non-tabular data for our analyses; cluster analyses that make large data sets tangible and raise new questions; time series analyses to understand trends, as well as econometric methods to test our hypotheses.