Why voters turn out on Election Day has eluded a straightforward explanation. Rational choice theorists have proposed a parsimonious model, but its logical implication is that hardly anyone would vote since their one vote is unlikely to determine the election outcome. Attempts to save the rational choice model incorporate factors like the expressive benefits of voting, yet these modifications seem to be at odds with core assumptions of rational choice theory. Still, some people do weigh the expected costs and benefits of voting and take account of the closeness of the election when deciding whether or not to vote. Many more, though, vote out of a sense of civic duty. In contrast to the calculus of voting model, the civic voluntarism model focuses on the role of resources, political engagement, and to a lesser extent, recruitment in encouraging people to vote. It pays particular attention to the sources of these factors and traces complex paths among them. There are many other theories of why people vote in elections. Intergenerational transmission and education play central roles in the civic voluntarism models. Studies that link official voting records with census data provide persuasive evidence of the influence of parental turnout. Education is one of the best individual-level predictors of voter turnout, but critics charge that it is simply a proxy for pre-adult experiences within the home. Studies using equally sophisticated designs that mimic the logic of controlled experiments have reached contradictory conclusions about the association between education and turnout. Some of the most innovative work on voter turnout is exploring the role of genetic influences and personality traits, both of which have an element of heritability. This work is in its infancy, but it is likely that many genes shape the predisposition to vote and that they interact in complex ways with environmental influences. Few clear patterns have emerged in the association between personality and turnout. Finally, scholars are beginning to recognize the importance of exploring the connection between health and turnout.
Gaurav Sood and Yphtach Lelkes
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.
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.
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.
Thomas J. Leeper
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.
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).
Wouter van Atteveldt, Kasper Welbers, and Mariken van der Velden
Analyzing political text can answer many pressing questions in political science, from understanding political ideology to mapping the effects of censorship in authoritarian states. This makes the study of political text and speech an important part of the political science methodological toolbox. The confluence of increasing availability of large digital text collections, plentiful computational power, and methodological innovations has led to many researchers adopting techniques of automatic text analysis for coding and analyzing textual data. In what is sometimes termed the “text as data” approach, texts are converted to a numerical representation, and various techniques such as dictionary analysis, automatic scaling, topic modeling, and machine learning are used to find patterns in and test hypotheses on these data. These methods all make certain assumptions and need to be validated to assess their fitness for any particular task and domain.
Kevin Arceneaux and Martin Johnson
Students of public opinion tend to focus on how exposure to political media, such as news coverage and political advertisements, influences the political choices that people make. However, the expansion of news and entertainment choices on television and via the Internet makes the decisions that people make about what to consume from various media outlets a political choice in its own right. While the current day hyperchoice media landscape opens new avenues of research, it also complicates how we should approach, conduct, and interpret this research. More choices means greater ability to choose media content based on one’s political preferences, exacerbating the severity of selection bias and endogeneity inherent in observational studies. Traditional randomized experiments offer compelling ways to obviate these challenges to making valid causal inferences, but at the cost of minimizing the role that agency plays in how people make media choices. Resent research modifies the traditional experimental design for studying media effects in ways that incorporate agency over media content. These modifications require researchers to consider different trade-offs when choosing among different design features, creating both advantages and disadvantages. Nonetheless, this emerging line of research offers a fresh perspective on how people’s media choices shapes their reaction to media content and political decisions.
Yotam Shmargad and Samara Klar
The field of political science is experiencing a new proliferation of experimental work, thanks to a growth in online experiments. Administering traditional experimental methods over the Internet allows for larger and more accessible samples, quick response times, and new methods for treating subjects and measuring outcomes. As we show in this chapter, a rapidly growing proportion of published experiments in political science take advantage of an array of sophisticated online tools. Indeed, during a relatively short period of time, political scientists have already made huge gains in the sophistication of what can be done with just a simple online survey experiment, particularly in realms of inquiry that have traditionally been logistically difficult to study. One such area is the important topic of social interaction. Whereas experimentalists once relied on resource- and labor-intensive face-to-face designs for manipulating social settings, creative online efforts and accessible platforms are making it increasingly easy for political scientists to study the influence of social settings and social interactions on political decision-making. In this chapter, we review the onset of online tools for carrying out experiments and we turn our focus toward cost-effective and user-friendly strategies that online experiments offer to scholars who wish to not only understand political decision-making in isolated settings but also in the company of others. We review existing work and provide guidance on how scholars with even limited resources and technical skills can exploit online settings to better understand how social factors change the way individuals think about politicians, politics, and policies.