Erin McGrath joined the START Consortium at the University of Maryland at College Park as NSF Post-doctoral Research Associate in Computational Social Science in August 2015, and received her doctorate in Public and International Affairs at the Graduate School of Public and International Affairs at the University of Pittsburgh in the same year. Her research interests can be summarized as approaching intractable policy problems for socia l good through inter-disciplinary cooperation, creativity, and computation. Currently, her work focuses on improving the measurement of grievance to predict conflict, and the rise of popular authoritarianism with a focus on contemporary Turkey.
Abstract: How does grievance affect the level, timing, and location of contention throughout election periods? Existing measures drawn from political, economic, or demographic sources capture limited variation over time and space. We capture individual expressions on social media around national-level votes in elections, impacting perceptions about current and future states of relative deprivation. From Twitter data we extract sentiment, and perform a Bayesian hierarchical model with the new indicator and traditional measures of grievance to explain political instability around recent elections in Sub-Saharan African countries.
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