Matthew Simonson
Networks | Conflict | Protest
Teaching
Protest, Political Violence, and Rebellion
Undergraduate, 2 credits
This course aims to provide you with a broad introduction to “contentious politics,” a term that encompasses protest, terrorism, and armed rebellion. Why do some revolutions succeed, while others fail? Is nonviolence effective? Do attacks on civilians usually backfire? Why do some movements create highly visible armies while others maintain a hidden network of terrorist cells? To explore these questions, the course combines classic works of political science and sociology with the latest data-driven research. In the process, we will learn how scholars of contentious politics test their theories, on what matters there is general agreement, and where debate still rages.
Experiments, Quasi-Experiments, and Causal Inference
Graduate, 4 credits (year-long)
Undergraduate 2-credit version: "3rd Year Honors Seminar: Correlation and Causation"
This course will teach you to answer the question “Does X actually cause Y or are they merely correlated?” We will begin by looking at randomized experiments including:
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a survey experiment testing how a hypothetical candidate’s ethnicity, age, and religion affects their popularity with voters
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a field experiment that randomly assigns female police officers to districts without any
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an evaluation of programs aimed at discouraging former rebels from joining criminal gangs
We will also discuss the ethics, practicalities, and limitations of experiments—and design our own. The course then turns to “natural experiments” and “quasi-experiments” such as:
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the impact of a new policy that is being gradually phased in (e.g., comparing districts where the policy has already been implemented to those where it has not)
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the legacy of colonialism on democratic values (e.g., comparing villages falling on one side of an arbitrary colonial border to those on the other)
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how a monarch’s gender impact’s foreign policy (e.g., comparing European monarchs who, by chance, had no sons and were thus succeed by a queen instead of a king)
These natural and quasi-experiments—which tend to be partially but not completely random—require more advanced statistical tools. Therefore, we will learn R, a programming language that has become the standard among the newest generation of political scientists.
Network Theory and Analysis
Graduate, 2 credits
Humans live in a web of relationships. Our ideas and attitudes are influenced by those of people we come in contact with, both online and face-to-face. We join social movements, rebel armies, sports clubs, and religious communities, in part, because of whom we know. Political parties, states, tribes, and terrorist groups, and street gangs form rivalries and alliances not in isolation, but in response to a broader web of rivalries and alliances with other actors. Understanding networks, therefore, is crucial to understanding our social and political world. While the emphasis of this course is on the role of networks in political science—and to some extent, communications and sociology—the techniques we use also have applications to networks in ecology, genetics, physics, anthropology, and economics. We will learn network theory and then practice analyzing network data in R. To do so, students will read a textbook chapter and an academic article each week, as well as completing practice exercises begun in class.
American Political Thought and Behavior
Graduate, 4 credits (year-long)
Co-Taught with Charlie Lesch
From its founding until the present, the United States has cultivated a unique and influential tradition of political thought. Concurrently, it represents a valuable site for the study of key questions in political behavior. In this seminar, we survey American political thought and behavior by focusing on how each were and continue to be shaped by social, political, and philosophical elements distinctive to the United States. By joining normative, interpretive, and historical approaches from political theory with the empirical study of behavior and institutions, this course aims to equip students with a knowledge of American politics spanning the diverse subfields of political science.
Social Science Methods Bootcamp: Intermediate Statistic in R
Graduate, 2 credits
This is a weeklong methodology bootcamp aimed at social science graduate students who have completed an introductory methods course and wish to extend their statistical capabilities. Third-year BA students who have taken a quantitative methods course are also welcome. Each day consists of three lectures and two practice sessions. The curriculum centers on two key topics that are widespread in contemporary political science research: generalized linear models (e.g., logit, probit, conditional logit, negative binomial) and multilevel modeling (e.g., fixed effects, random effects, mixed effects). Students will learn to clean data, run regressions, and create customized plots using the R programming language (no experience needed). Other topics include probability notation, matrix algebra, weighted least squares, bootstrapping, cross-validation, and regularization.