Browsing by Author "Ward, Michael D"

Event data provide high-resolution and high-volume information about political events. From COPDAB to KEDS, GDELT, ICEWS, and PHOENIX, event datasets and the frameworks that produce them have supported a variety of research efforts across fields and including political science. While these datasets are machine-coded from vast amounts of raw text input, they nonetheless require substantial human effort to produce and update sets of required dictionaries. I introduce a novel method for generating large dictionaries appropriate for event-coding given only a small sample dictionary. This technique leverages recent advances in natural language processing and deep learning to greatly reduce the researcher-hours required to go from defining a new domain-of-interest to producing structured event data that describes that domain. An application to cybersecurity is described and both the generated dictionaries and resultant event data are examined. The cybersecurity event data are also examined in relation to existing datasets in related domains.

In situations of armed violence and insecurity, how do civilians influence the political environment around them? In this dissertation, I present three different studies that broadly engage this question. In concert, the papers presented herein offer new insights on civilians' relationship to armed conflict through a focus on victimization, participation, attitudes on resistance, and the effects of civilian resistance on aggregate levels of violence.

The first study explores the effects of victimization on political participation. I argue that previous answers to this question have overlooked a key variable for predicting civilian behavior: individual level social context. As a step forward in connecting social support networks to behavioral outcomes, I present the kinship network as a novel measure that captures an individual's valuable and private social interactions. I find that survivors of criminal violence with strong ties to kinship networks are most likely to attend political meetings. By highlighting variation in behavior across victims, I challenge previous work which only examines differences in participation between victims and non-victims.

Motivated by the assumption that attitudes are a precursor to action, my second study examines civilian attitudes on the efficacy of resistance in regions of protracted violence. Using an original survey fielded in Mexico, I explore the conditions under which civilians are likely to view nonviolent or violent methods as useful tools for change. I first test whether several demographic factors--age, gender, income, knowledge about civil resistance, and media consumption--influence attitudes toward resistance. Moving beyond these variables, I then test whether perceptions about government responsibility affect these attitudes. Specifically, I argue that civilian attitudes towards resistance methods are informed by which political actor civilians view as responsible for their security problems. I find that the predicted probability of viewing nonviolent action as more effective than violent action increases by 20.8% for those who attribute security responsibility to local authorities, compared to other actors. Using an embedded survey experiment, I then address the empirically relevant question of whether these attitudes about resistance correlate with action. I find that compared to those who do not view resistance as useful, respondents who view nonviolence as effective are "supportive types'' who are more willing than others to support local resistance groups, regardless of the methods these groups employ. Together, these analyses provide important information for civilian organizers seeking to mobilize latent support for resistance. Moreover, they enrich our understanding of the ways in which communities can reduce violence in order to reclaim political control during armed conflicts.

Last, I present an aggregated analysis on the evolution of armed conflict in Mexico. The criminal war in Mexico is extremely complex: Drug Trafficking Organizations, citizens, government agents, amongst others, are all relevant actors within the dynamic evolution of the conflict. Existing research, however, typically ignores the interdependencies inherent to these networks. Using a new collection of machine-coded event data, I generate conflict networks for each year from 2004 to 2010. In doing so, I make three major contributions. First, I offer insights into the potential promise and pitfalls of using machine-coded data for country-level analysis. Next, after cleaning and improving upon the original data, I generate yearly networks, which capture a wide range of violent-related actors. Importantly, I demonstrate how these networks illustrate the interdependent nature of the Mexican conflict and present new insights, such as how government coordination changes in response to cartel violence over time. Finally, I use a latent space approach to identify previously unobservable violence between government actors, criminal groups, and civilians. This research design serves as a platform for future research to investigate the effects of major civilian-led events--such as mass protests--on the evolution of armed conflict.

Critiquing dyads as the unit of analysis in statistical work has become increasingly prominent; a number of scholars have demonstrated that ignoring the interdependencies and selection effects among dyads can bias our inference. My dissertation argues that the problem is even more serious. The bargaining model relies on the assumption that bargaining occurs between two states in isolation. When we relax this assumption one of the most crucial findings of these bargaining models vanishes: it is no longer irrational, even with complete information and an absence of commitment issues, for states to go to war. By accounting for the non-dyadic nature of interstate relations, we are better able to explain a number of empirical realities, and better able to predict when states will go to war.

In the first chapter of my dissertation I model a bargaining episode between three players and demonstrate its marked divergence from canonical bargaining models. In traditional two player bargaining models, it is irrational for states to go to war. I find this irrationality of war to be in part an artifact of limiting the focus to two players. In the model in chapter one, three states are bargaining over policy, and each state has a preference in relation to this policy. When these preferences diverge enough, it can become impossible for players to resolve their disputes peacefully. One implication of this model is that differences between two and three player bargaining is not just a difference in degree, but a difference in kind. The model in this chapter forms the core of the writing sample enclosed. Chapter two tests whether my own model is just an artifact of a particular set of assumptions. I extend the bargaining model to allow for N-players and modify the types of policies being bargained over, and I find that not only do the results hold, in many cases they are strengthened. The second chapter also changes chapter one's model so states are bargaining over resources rather than policy which results in a surprising finding: while we might expect states to be more willing to fight in defense of the homeland than over a policy, if more than two states are involved, it is in fact the disputes over territory that are significantly more peaceful.

In the final chapter of my dissertation, I attempt to apply the insights from the theoretical chapters to the study of interstate conflict and war. In particular, I compare a purely dyadic model of interstate crises to a model that accounts for non-dyadic interdependencies. The non-dyadic model that I present is an Additive and Multiplicative Effects Network model, and it substantially outperforms the traditional dyadic model, both in explaining the variance of the data and in predicting out of sample. By combining the theoretical work in the earlier chapters with the empirical work in the final chapter I can show that not only do dyadic models limit our ability to model the causes of conflict, but that by moving beyond the dyad we actually get notable gains in our ability to understand the world and make predictions.

A foreign direct investment (FDI) project can only materialize with the consent of both the multinational corporation (MNC) and the host country. However, the literature on FDI has focused only on the preference of MNCs, assuming that all countries are eager to receive FDI. Through various case studies, I show that countries have varied and strategic preference, playing a substantial role in determining where FDI locates. Failing to recognize this two-sided matching nature of the FDI market, not only do existing models of FDI produce wrong estimates of MNCs' preference, they also prevent us from investigating countries' preference. I introduce the two-sided matching model, investigate properties of the model, and apply it to study Japanese FDI in Southeast Asia. I show how to estimate the preference of both MNCs and countries for one another, modeling the two-sided matching process behind FDI location that scholars have always known but never been able to study quantitatively. With this model, scholars can better understand of what drives FDI location and policy makers can better simulate FDI movement under hypothetical policy changes.

My research is driven by two questions: Why do some dissident groups choose nonviolence over violence while others prefer violence over nonviolence? Why do political movements, even those using the same tactics, unfold and evolve divergently? To answer the first question, I argue that nonviolent dissidents are dependent on human resources and violent dissidents are dependent on physical resources. Further, either strategy could be more costly, depending on the strategic environment in which the resistance movement takes place. For the second question, I contend that the opposition which poses a level of threat greater than the cost of policy change gains concession in a prolonged movement. Oppositions that are unable to sustain their activities do not constitute a credible threat and therefore are defeated rather swiftly. Finally, every process requires time and therefore a movement's duration should explain the outcome of significant progress. By analyzing 250 political movements of various types around the world, I provide empirical evidence to support my theory. To complement the large-N empirical analysis, an in-depth analysis of two movements (one violent and one nonviolent) in India is provided.

Ostensibly, BITs are the ideal international treaty. First, until just recently, they almost uniformly came with explicit dispute resolution mechanisms through which countries could face real costs for violation (Montt 2009). Second, the signing, ratification, and violation of them are easily accessible public knowledge. Thus countries presumably would face reputational costs for violating these agreements. Yet, these compliance devices have not dissuaded states from violating these agreements. Even more interestingly, in recent years, both developed and developing countries have moved towards modifying the investor-friendly provisions of these agreements. These deviations from the expectations of the credible commitment argument raise important questions about the field's assumptions regarding the ability of international treaties with commitment devices to effectively constrain state behavior.

The Arab Spring has renewed scholarly interest in popular protests and nonviolent mobilization against authoritarian rulers. Over the past decade, the bulk of the literature has focused on examining the impact of protest movements on regime transition, while lesser attention was paid to explain why protests emerge initially. Social movements literature has documented rich materials on contentious politics; however, as Tilly, Tarrow, and McAdam (2001) indicated in their seminal work, these traditional approaches work better to explain contention in democracies but less well when it comes to explaining protests in nondemocratic contexts. My dissertation, a suite of three related papers, aims to fill this gap by asking several important questions: Why do citizens risk their lives to protest against the authoritarian governments under the threats of state repression? How does mobilization behaviors interact with state responses (e.g. state repression)? Why do opposition parties participate and mobilize protesters in authoritarian elections? Using new protest event data, I first show that in authoritarian China, politically motivated officials are encouraged to compete in the economic field by extracting local resources, and these efforts often contribute to local protests. Additional evidence also indicates that land expropriation by local governments has become the main source of social grievance in contemporary China. Second, I show that mobilization behaviors and state responses are intrinsically interdependent to each other. I propose a network method to model this interdependence and interactive repertoires of contention. I find that the nodes-as-actions framework I introduce improves our ability to forecast different types of state repression against protesters and helps us examine the processes of conflict escalation and a mutual spiral effect in authoritarian elections. Lastly, I find that anti-government protest mobilization is an oft-used electoral campaign strategy by the opposition to mobilize supporters, gain visibility in state censorship, and signal their strength and commitment to unseating autocratic rulers in authoritarian elections. When the authoritarian incumbent suffers from declining popularity among citizens, it provides a window of opportunity for the opposition candidates to defeat the authoritarian ruler on the ballot by mobilizing anti-regime protesters and encouraging voter turnout. Overall, this dissertation introduces novel theoretical framework and empirical methods to advance our understanding of protest emergence in authoritarian regimes.