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Article

The news media have been disrupted. Broadcasting has given way to narrowcasting, editorial control to control by “friends” and personalization algorithms, and a few reputable producers to millions with shallower reputations. Today, not only is there a much broader variety of news, but there is also more of it. The news is also always on. And it is available almost everywhere. The search costs have come crashing down, so much so that much of the world’s information is at our fingertips. Google anything and the chances are that there will be multiple pages of relevant results. Such a dramatic expansion of choice and access is generally considered a Pareto improvement. But the worry is that we have fashioned defeat from the bounty by choosing badly. The expansion in choice is blamed for both, increasing the “knowledge gap,” the gap between how much the politically interested and politically disinterested know about politics, and increasing partisan polarization. We reconsider the evidence for the claims. The claim about media’s role in rising knowledge gaps does not need explaining because knowledge gaps are not increasing. For polarization, the story is nuanced. Whatever evidence exists suggests that the effect is modest, but measuring long-term effects of a rapidly changing media landscape is hard and may explain the results. As we also find, even describing trends in basic explanatory variables is hard. Current measures are beset with five broad problems. The first is conceptual errors. For instance, people frequently equate preference for information from partisan sources with a preference for congenial information. Second, survey measures of news consumption are heavily biased. Third, behavioral survey experimental measures are unreliable and inapt for learning how much information of a particular kind people consume in their real lives. Fourth, measures based on passive observation of behavior only capture a small (likely biased) set of the total information consumed by people. Fifth, content is often coded crudely—broad judgments are made about coarse units, eliding over important variation. These measurement issues impede our ability to answer the extent to which people choose badly and the attendant consequences of such. Improving measures will do much to advance our ability to answer important questions.

Article

Recognizing its causal power, contemporary scholars of media effects commonly leverage experimental methodology. For most of the 20th century, however, political scientists and communication scholars relied on observational data, particularly after the development of scientific survey methodology around the mid-point of the century. As the millennium approached, Iyengar and Kinder’s seminal News That Matters experiments ushered in an era of renewed interest in experimental methods. Political communication scholars have been particularly reliant on experiments, due to their advantages over observational studies in identifying media effects. Although what is meant by “media effects” has not always been clear or undisputed, scholars generally agree that the news media influences mass opinion and behavior through its agenda-setting, framing, and priming powers. Scholars have adopted techniques and practices for gauging the particular effects these powers have, including measuring the mediating role of affect (or emotion). Although experiments provide researchers with causal leverage, political communication scholars must consider challenges endemic to media-effects studies, including problems related to selective exposure. Various efforts to determine if selective exposure occurs and if it has consequences have come to different conclusions. The origin of conflicting conclusions can be traced back to the different methodological choices scholars have made. Achieving experimental realism has been a particularly difficult challenge for selective exposure experiments. Nonetheless, there are steps media-effects scholars can take to bolster causal arguments in an era of high media choice. While the advent of social media has brought new challenges for media-effects experimentalists, there are new opportunities in the form of objective measures of media exposure and effects.

Article

Mathew V. Hibbing, Melissa N. Baker, and Kathryn A. Herzog

Since the early 2010s, political science has seen a rise in the use of physiological measures in order to inform theories about decision-making in politics. A commonly used physiological measure is skin conductance (electrodermal activity). Skin conductance measures the changes in levels of sweat in the eccrine glands, usually on the fingertips, in order to help inform how the body responds to stimuli. These changes result from the sympathetic nervous system (popularly known as the fight or flight system) responding to external stimuli. Due to the nature of physiological responses, skin conductance is especially useful when researchers hope to have good temporal resolution and make causal claims about a type of stimulus eliciting physiological arousal in individuals. Researchers interested in areas that involve emotion or general affect (e.g., campaign messages, political communication and advertising, information processing, and general political psychology) may be especially interested in integrating skin conductance into their methodological toolbox. Skin conductance is a particularly useful tool since its implicit and unconscious nature means that it avoids some of the pitfalls that can accompany self-report measures (e.g., social desirability bias and inability to accurately remember and report emotions). Future decision-making research will benefit from pairing traditional self-report measures with physiological measures such as skin conductance.

Article

Benjamin R. Knoll and Cammie Jo Bolin

Religious communication affects political behavior through two primary channels: political messages coming from a religious source and religious messages coming from a political source. In terms of the first channel, political scientists have found that clergy do tend to get involved in politics, and church-goers often hear political messages over the pulpit, although not as frequently as might be expected. Sometimes these political messages are successful in swaying opinions, but not always; context matters a great deal. In terms of the second channel, politicians use religious rhetoric (“God talk”) in an attempt to increase their support and win votes. When this happens, some groups are more likely to respond than others, including political conservatives, more frequent church attenders, and racial/ethnic minorities. The scope and effectiveness of religious communication remains a field ripe for further research, especially in contexts outside of the United States.

Article

Empirical media effects research involves associating two things: measures of media content or experience and measures of audience outcomes. Any quantitative evidence of correlation between media supply and audience response—combined with assumptions about temporal ordering and an absence of spuriousness—is taken as evidence of media effects. This seemingly straightforward exercise is burdened by three challenges: the measurement of the outcomes, the measurement of the media and individuals’ exposure to it, and the tools and techniques for associating the two. While measuring the outcomes potentially affected by media is in many ways trivial (surveys, election outcomes, and online behavior provide numerous measurement devices), the other two aspects of studying the effects of media present nearly insurmountable difficulties short of ambitious experimentation. Rather than find solutions to these challenges, much of collective body of media effects research has focused on the effort to develop and apply survey-based measures of individual media exposure to use as the empirical basis for studying media effects. This effort to use survey-based media exposure measures to generate causal insight has ultimately distracted from the design of both causally credible methods and thicker descriptive research on the content and experience of media. Outside the laboratory, we understand media effects too little despite this considerable effort to measure exposure through survey questionnaires. The canonical approach for assessing such effects: namely, using survey questions about individual media experiences to measure the putatively causal variable and correlating those measures with other measured outcomes suffers from substantial limitations. Experimental—and sometimes quasi-experimental—methods provide definitely superior causal inference about media effects and a uniquely fruitful path forward for insight into media and their effects. Simultaneous to this, however, thicker forms of description than what is available from close-ended survey questions holds promise to give richer understanding of changing media landscape and changing audience experiences. Better causal inference and better description are co-equal paths forward in the search for real-world media effects.

Article

Christina Ladam, Ian Shapiro, and Anand Sokhey

As the most common form of voluntary association in America, houses of worship remain an unquestionably critical component of American civil society. Major approaches to studying religion and politics in the United States are described, and the authors present an argument for focusing more attention on the organizational experience provided by religious contexts: studying how individuals’ social networks intersect with their associational involvements (i.e., studying religion from a “interpersonal” perspective) may actually shed new light on intrapersonal, psychological constructs like identity and religiosity. Evidence is presented from two nationally representative data sets that suggests considerable variance in the degree to which individuals’ core social networks overlap with their houses of worship. This variance exists within and between individuals identifying with major religious traditions, and such networks are not characterized solely by agreement (as theories of self-selection might suggest).

Article

The “sunk costs fallacy” is a popular import into political science from organizational psychology and behavioral economics. The fallacy is classically defined as a situation in which decision-makers escalate commitment to an apparently failing project in order to “recoup” the costs they have already sunk into it. The phenomenon is often framed as a good example of how real decision-making departs from the assumption of forward-looking rationality which underpins traditional approaches to understanding politics. Researchers have proposed a number of different psychological drivers for the fallacy, such as cognitive dissonance reduction, and there is experimental and observational evidence that it accurately characterizes decision-making in certain contexts. However, there is significant skepticism about the fallacy in many social sciences, with critics arguing that there are better forward-looking rational explanations for decisions apparently driven by a desire to recoup sunk costs – among them reputational concerns, option values and agency problems. Critics have also noted that in practical situations sunk costs are informative both about decision makers’ intrinsic valuation for the issue and the prospects for success, making it hard to discern a separate role for sunk costs empirically. To address these concerns, empirical researchers have employed a number of strategies, especially leveraging natural experiments in certain non-political decision making contexts such as sports or business, in order to isolate the effects of sunk costs per se from other considerations. In doing so, they have found mixed support for the fallacy. Research has also shown that the prevalence of the sunk costs fallacy may be moderated by a number of factors, including the locus of decision-making, framing, and national context. These provide the basis for suggestions for future research.