“Big data” in the form of unstructured text pose challenges and opportunities to social scientists committed to advancing research frontiers. Because machine-based and human-centric approaches to content analysis have different strengths for extracting information from unstructured text, the authors argue for a collaborative, hybrid approach that combines their comparative advantages.

Domestic political support is an important factor constraining the use of American military power around the world. Although the dynamics of war support are thought to reflect a cost-benefit calculus, with costs represented by numbers of friendly war deaths, no previous study has examined how information about friendly, enemy, and civilian casualties is routinely presented to domestic audiences. This article establishes a baseline measure of historical casualty reporting by examining New York Times coverage of five major wars that occurred over the past century.

On August 30, 2013, the American Political Science Association sponsored a roundtable on political epistemology as part of its annual meetings. Co-chairing the roundtable were Jeffrey Friedman, Department of Government, University of Texas at Austin; and Hélène Landemore, Department of Political Science, Yale University.

Political communication research often claims that empirical findings are important or relevant for democratic politics without identifying the value judgments that support these assertions. Because these value judgments often lurk in the background as unstated premises, empirical scholars frequently advance normative claims about the importance or relevance of their findings without being aware that they are doing so. This chapter introduces normative assessment as a way to advance the horizons of political communication research by bringing these usually hidden claims to light.

The “proximate casualties” hypothesis holds that popular support for American wars is undermined more by the deaths of American personnel from nearby areas than by the deaths of those from far away. However, no previous research has tested the mechanisms that might produce this effect.

Mass communication researchers have an interest in accurately measuring media exposure. Survey measures often ask respondents about the number of days in a week or the hours in a day that they use a medium. These two strategies (and their composite-- hours per week) have yet to be directly compared to one another; so their relative usefulness for researchers is unknown. Analyses of data from the 2008 American National Election Studies Time Series Study suggest few benefits from measuring news exposure using both approaches.

News outlets cannot serve as reliable conveyors of social facts, nor do their audiences crave such content. Nonetheless, much political science scholarship assumes that objective information about social, political, and economic topics is routinely transmitted to the mass public through the news. This article addresses the problem of selection bias in news content and illustrates the problem with a content analytic study of New York Times coverage given to American war deaths in five major conflicts that occurred over the past century.

Contemporary theories of opinion dynamics—exemplified by Zaller's “receive-accept-sample” model—tend to assume that attitude change should occur only following exposure to new, attitude-relevant information. Within this prevailing view, the expected direction and magnitude of opinion change is largely a function of the tone and content of the new information to which one is exposed. In contrast, social identification theories show how opinion change can occur when a person's environmental context activates social knowledge stored in long-term memory.

The degree to which people seek and retain information about politics is a key variable for understanding why people think, feel, and act as they do politically. But measuring information acquisition has proven to be fraught with challenges. As a consequence, in recent years political scientists have shifted their measurement strategies to focus on information retention, most commonly in the form of factual knowledge questions.