A Big Data Methodology for Bridging Quantitative and Qualitative Political Science Research

Sliva, A. and Neal Reilly, S.

American Political Science Association 2014 Annual Meeting, Washington, DC (2014)

The spread of digital technologies has led to a massively interconnected global system that creates and transmits astronomical quantities of data. This “information explosion” impacts the ways we can study and understand the dynamics of socio-political systems by increasing the variety, availability, and complexity of the data available to both qualitative and quantitative political scientists. These new information sources can, importantly, also support mixed methods approaches that can be more effective than either pure approach. However, researchers currently lack the appropriate tools to fully leverage this wealth of information. In this paper, we present a new technology-based methodological framework—the Model Analyst’s Toolkit (MAT)—that can support mixed methods research designs. As a use case, we focus on the particularly challenging analytic task of establishing causal models and illustrate how this methodological approach can enable experts of all backgrounds to use data visualization, modeling, and validation tools to enhance their findings in the evolving digital information environment.

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