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Gokhan Ciflikli is a Research Officer in Analytic Software Development in the Methodology Department at the London School of Economics. His main responsibility is to develop a scalable Shiny app for the quanteda package in R for social scientists at large. His PhD investigates the common predictive covariates of war duration, which was completed at the LSE. Previously, he was a visiting scholar at UC Berkeley, and a Researcher at the Uppsala Conflict Data Program (UCDP). He holds a Master’s degree in Peace and Conflict Studies from Uppsala University, Sweden.
Gokhan’s research interests lie primarily within computational social science and political methodology. More specifically, he focuses on the prediction of armed conflict using ensemble models; problematisation of the fidelity vs. interpretability trade-off in machine learning; quantitative text analysis and natural language processing of time-series data; and the measurement and quantification of issues of representation and bias in social sciences. He co-teaches the quantitative text analysis course MY459 for the MSc in Applied Social Data Science.
Interpretable Machine Learning;
Natural Language Processing (NLP);
Forecasting Armed Conflict;
Civil War Dynamics;
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