Data & Methods
One of the challenges facing social scientists is the failure to predict election outcomes. This phenomenon raises questions of whether theories and models developed in the past apply in the current environment. Concurrently, the abundance of online, social media data provides social scientists with opportunities to understand today's social and political phenomena. To use such opportunities, however, important issues on how to process and use social media need to be addressed. The research team will carry out a few parallel projects with the unifying theme of integrating geospatial, social media and spatial data to address research and methodological questions. One project is about communication patterns and their effects on political choices and behavior in the 2016 presidential election. The second project investigates online and Twitter communication about parenting information and misinformation. A third project will investigate a variety of methodological issues associated with inferences drawn from probability-based and nonprobability-based social surveys and from social media. The three projects will employ methods of cross-validation of survey data, social media, and administrative records and investigate the social network dynamics of elites and the general public. The project is a collaboration between researchers from multiple units at the University of Michigan and at Georgetown University, and the team will also engage researchers at Gallup. This set of projects will become the locus for multidisciplinary efforts between social scientists, computer scientists, and statisticians at both institutions, and each university will become the locus for future extended work of this kind. The data science tools developed through this set of projects will also have wide application to other research questions in social science.
Michigan Institute for Data Science (MIDAS)- Data Science Initiative
- Michael W. Traugott
- Trivellore E. Raghunathan
2017-03-01 - 2020-02-28