The Transition from Quantitative to Computational Methods in Foreign Policy Analysis

Computational methods have been increasingly used in Foreign Policy Analysis (FPA). Text analysis, geospatial analysis, and network analysis are among the most used computational methods. This article examines the FPA literature that utilizes computational methods and discusses their theoretical and empirical implications for future research. I argue that while these methods are not without their criticisms, the integration of computational tools enables FPA researchers to create and use big data sets, improve sampling, and collect and analyze data. Computational methods in FPA enable theory-driven analysis of big data, providing both theoretical and empirical insights, and allowing testing of micro-level foundations of FPA theories. However, challenges such as the validity of measures and selection bias should be taken into account. While computational methods present significant opportunities for advancing FPA, these challenges need consideration.