Contemporary dictionary-based approaches to sentiment analysis exhibit serious validity problems when applied to specialized vocabularies, but human-coded dictionaries for such applications are often labor-intensive and inefficient to develop. We demonstrate the validity of “minimally-supervised” approaches for the creation of a sentiment dictionary from a corpus of text drawn from a specialized vocabulary. We demonstrate the validity of this approach in estimating sentiment from texts in a large-scale benchmarking dataset recently introduced in computational linguistics, and demonstrate the improvements in accuracy of our approach over well-known standard (nonspecialized) sentiment dictionaries. Finally, we show the usefulness of our approach in an application to the specialized language used in US federal appellate court decisions.

Beginning in 1999, Curtis Signorino challenged the use of traditional logits and probits analysis for testing discrete-choice, strategic models. Signorino argues that the complex parametric relationships generated by even the simplest strategic models can lead to wildly inaccurate inferences if one applies these traditional approaches. In their stead, Signorino proposes generating stochastic formal models, from which one can directly derive a maximum likelihood estimator. We propose a simpler, alternative methodology for theoretically and empirically accounting for strategic behavior. In particular, we propose carefully and correctly deriving one's comparative statics from one's formal model, whether it is stochastic or deterministic does not particularly matter, and using standard logit or probit estimation techniques to test the predictions. We demonstrate that this approach performs almost identically to Signorino's more complex suggestion.

A common problem in models for dichotomous dependent variables is “separation,” which occurs when one or more of a model's covariates perfectly predict some binary outcome. Separation raises a particularly difficult set of issues, often forcing researchers to choose between omitting clearly important covariates and undertaking post—hoc data or estimation corrections. In this article I present a method for solving the separation problem, based on a penalized likelihood correction to the standard binomial GLM score function. I then apply this method to data from an important study on the postwar fate of leaders.

As applications of duration analysis have burgeoned in political science, scholars have become increasingly aware of the potential substantive importance of duration dependence: the extent to which the conditional hazards of the events of interest are rising or falling over time. Here I discuss the issue of duration dependence, focusing on the distinction between “spurious” dependence due to unobserved heterogeneity and “true” duration dependence due to state dependence in the process of interest. I present a simple extension of a commonly used parametric duration model—the Weibull model—which allows researchers to assess the influence of causal variables on the nature and extent of duration dependence in their data. I then illustrate the application of this “generalized Weibull” model using data on the duration of international alliances.

Existing work on the U.S. separation of powers typically views the Supreme Court as the final arbiter of constitutional and statutory disputes. By contrast, much comparative work explicitly recognizes the role of executives in enforcing and implementing court decisions. Drawing on that work, this study relaxes the assumption that executives must comply with Supreme Court rulings, and instead allows the propensity for executive compliance to depend upon indirect enforcement by the public. We develop a simple model of Supreme Court decision making in the presence of executive discretion over compliance and demonstrate that such discretion can restrict substantially the Court’s decision making. Using data collected for the Warren and Burger courts, we find evidence consistent with the argument that the Supreme Court’s ability to constrain exective descretion depends critically upon the public.

It has been widely speculated that violent conflict acts as a key contributor to the transmission of human immunodeficiency virus (HIV). Yet to date no empirical examination of the conflict-HIV relationship has been conducted. Drawing on work in political science and public health, we set forth a theoretical framework for understanding this potential relationship and go on to present data on the spatio-temporal dispersion of HIV/AIDS in 43 African countries during the period from 1997 to 2005. We then assess the association between domestic and international conflict and levels of HIV/AIDS infection while controlling for a range of other influential factors. Our analyses support a clear positive relationship between both international and domestic conflict and climbing HIV/AIDS prevalence, as well as significant palliative effects for education and economic development on the incidence of HIV/AIDS.

After more than a decade of membership stability, the U.S. Supreme Court experienced a pair of vacancies following its 2004–2005 term. In July 2005, Justice Sandra Day O'Connor announced her intention to retire. It is widely believed that her own health, that of her husband, and the favorable political environment influenced her decision to step down in January 2006. In the interim, Chief Justice William Rehnquist, after struggling with ill health for many months, passed away on 3 September 2005, becoming the first sitting justice to die in more than five decades.

The killing of a head of state is among the most severe and consequential forms of political violence. But to date, there have been no systematic studies of the incidence of such assassinations, with the few existing case studies tending to emphasize the uniqueness of those events. Drawing on existing theories of social protest and contentious politics, we argue instead that institutional and sociopolitical factors should be important correlates of assassination. We examine empirically the implications of this theory, using data on the incidence of assassinations of heads of state between 1946 and 2000. Our findings suggest that institutional factors related to leadership succession, institutionalized power, and levels of repression interact to influence the occurrence of such killings. Notable in this respect is our conclusion that, while repressive leaders are at greater risk for assassination, the effect of repression is moderated by executive power, such that weak, repressive leaders in nondemocratic systems face the highest risk of assassination. Our findings dovetail neatly with the broader literature on other forms of insurgency, suggesting that assassinations are but one manifestation of the larger phenomenon of political violence.

A key question in debates over globalization is its effect on the welfare states in particular on welfare “retrenchments”: programmatic retractions of the scope and coverage of social programs. We conceptualize such retrenchments as discrete policy events; and we offer a comprehensive model of their occurrence that integrates domestic economic, political, and institutional factors as well as those related to the global economy. Our analysis of all such retrenchments in Organization for Economic Cooperation and Development (OECD) nations between 1978 and 1994 indicates that the effects of globalization are complex, with trade openness and financial liberalization clearly operating against such retrenchments but outward foreign direct investment perhaps pressuring for them. In addition, we uncover support for a dynamic of “self-limiting immoderation”: economic and demographic pressures for costly welfare expenditures provoke actions to roll back eligibility and benefit rates that link increasing numbers of unemployed and retired persons to increased social spending. In short, the same demographic pressures that gave often been noted to substantially drive welfare spending may trigger welfare cutbacks.Our thanks to A. A. Alderson, Bob Jackman, Lane Kenworthy, Joakim Palme, Duane Swank, John Stephen, and two anonymous reviewers for their helpful comments and discussions, as well as to Kendralin Freedman for her work preparing the final manuscript. All remaining errors are our own. Previous versions of this article were presented at the Annual Meetings of the American Political Science Association and the American Sociological Association. The views expressed herein are those of the authors and do not reflect the opinions of the National Science Foundation or the U.S. government. All data and commands necessary to replicate the analyses presented here are available at our Web site 〈http://polisci.emory.edu/zorn/HZ/index.html〉.

Of Time and Judicial Behavior: United States Supreme Court Agenda-Setting and Decision-Making, 1888–1997.

The effect of a nanometer confinement on the molecular dynamics of poly(methyl phenyl siloxane) (PMPS) was studied by dielectric spectroscopy (DS), temperature modulated DSC (TMDSC) and neutron scattering (NS). DS and TMDSC experiments show that for PMPS in 7.5 nm pores the molecular dynamics is faster than in the bulk which originates from an inherent length scale of the underlying molecular motions. At a pore size of 5 nm the temperature dependence of the relaxation times changes from a Vogel / Fulcher / Tammann like behavior to an Arrhenius one. At the same pore size Δcp vanishes. These results give strong evidence that the glass transition has to be characterized by an inherent length scale of the relevant molecular motions. Quasielastic neutron scattering experiments reveal a strong change even in the microscopic dynamic.

An important feature of most political events is their repeatability: nearly all political events reoccur, and theories of learning, path dependence, and institutional change all suggest that later events will differ from earlier ones. Yet, most models for event history analysis fail to account for repeated events, a fact that can yield misleading results in practice. We present a class of duration models for analyzing repeated events, discuss their properties and implementation, and offer recommendations for their use by applied researchers. We illustrate these methods through an application to widely used data on international conflict.

A critical element of decision making is the timing of choices political actors make; often when a decision is made is as critical as the decision itself. We posit a dynamic model of strategic position announcement based on signaling theories of legislative politics. We suggest that members who receive clear signals from constituents, interest groups, and policy leaders will announce their positions earlier. Those with conflicting signals will seek more information, delaying their announcement. We test several expectations by examining data on when members of the House of Representatives announced their positions on the North American Free Trade Agreement. We also contrast the timing model with a vote model, and find that there are meaningful differences between the factors influencing the timing of position announcements and vote choice. Our research allows analysts to interpret the process leading up to the House action and the end state of that process.