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
Don't Expose Yourself: Discretionary Exposure to Political Information
Gaurav Sood and Yphtach Lelkes
Article
Media-Effects Experiments in Political Decision Making
Bryan Gervais
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
Social Network Influence on Political Behavior in Religious Contexts
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
Studying Political Decision Making With Automatic Text Analysis
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.
Article
Using Online Experiments to Study Political Decision Making
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.
