Public Opinion Quarterly最新文献

To study human behavior, social scientists are increasingly collecting data from mobile apps and sensors embedded in smartphones. A major challenge of studies implemented on general population samples, however, is that participation rates are rather low. While previous research has started to investigate the factors affecting individuals' decision to participate in such studies, less is known about features of the study design which are under the researcher's control and can increase the acceptance of smartphone-based data collection methods. Guided by the Technology Acceptance Model, we varied study characteristics in a vignette experiment to examine their effect on individuals' willingness to download a research app on their smartphone. Data were collected from 1,876 members of the NORC AmeriSpeak Panel, a probability-based panel of the general population aged 18+ in the United States. Respondents were randomly assigned to eight vignettes and, after each vignette, were asked to rate their willingness to participate in the described hypothetical study. The results show that individuals are more willing to participate in smartphone-based studies where they have some control over the data collection process, by having the option either to temporarily switch off the data collection or to review the data before submission. Furthermore, they are more willing to participate in research to which they are invited via postal letter rather than receiving a postal letter plus a phone call from an interviewer who walks them through the app installation. Finally, unconditional incentives increase their willingness to engage with smartphone-based data collection over conditional incentives.

We use a unique panel of household survey data-the Austrian version of the European Union Statistics on Income and Living Conditions (SILC) for 2008-2011-which have been linked to individual administrative records on both state unemployment benefits and earnings. We assess the extent and structure of misreporting across similar benefits and between benefits and earnings. We document that many respondents fail to report participation in one or more of the unemployment programs. Moreover, they inflate earnings for periods when they are unemployed but receiving unemployment compensation. To demonstrate the impact of income source confusion on estimators, we estimate standard Mincer wage equations. Since unemployment is associated with lower education, the reports of unemployment benefits as earnings bias downward the returns to education. Failure to report unemployment benefits also leads to substantial sample bias when selecting on these benefits, as one might in estimating the returns to job training.

Research into cyber-conflict, public opinion, and international security is burgeoning, yet the field suffers from an absence of conceptual agreement about key terms. For instance, every time a cyberattack takes place, a public debate erupts as to whether it constitutes cyberterrorism. This debate bears significant consequences, seeing as the ascription of a "terrorism" label enables the application of heavy-handed counterterrorism powers and heightens the level of perceived threat among the public. In light of widespread conceptual disagreement in cyberspace, we assert that public opinion plays a heightened role in understanding the nature of cyber threats. We construct a typological framework to illuminate the attributes that drive the public classification of an attack as cyberterrorism, which we test through a ratings-based conjoint experiment in the United States, the United Kingdom, and Israel (N = 21,238 observations). We find that the public (1) refrains from labeling attacks by unknown actors or hacker collectives as cyberterrorism; and (2) classifies attacks that disseminate sensitive data as terrorism to a greater extent even than physically explosive attacks. Importantly, the uniform public perspectives across the three countries challenge a foundational tenet of public opinion and international relations scholarship that divided views among elites on foreign policy matters will be reflected by a divided public. This study concludes by providing a definitive conceptual baseline to support future research on the topic.

Existent research shows that affective polarization has been intensifying in some publics, diminishing in others, and remaining stable in most. We contribute to this debate by providing the most encompassing comparative and longitudinal account of affective polarization so far. We resort to a newly assembled dataset able to track partisan affect, with varying time series, in eighteen democracies over the last six decades. We present results based on two different operational measures of affective polarization: Reiljan's Affective Polarization Index, based on reported partisans only, and Wagner's weighted distance from the most liked party, based on the whole electorate. Our reassessment of affective polarization among partisans confirms that an intensifying trend is observable in a number of countries but it is, by no means, generalizable to all established democracies. Regarding the longitudinal assessment of affective polarization among the electorate, we confirm that US citizens have become more affectively polarized over time.

The debate around "fake news" has raised the question of whether liberals and conservatives differ, first, in their ability to discern true from false information, and second, in their tendency to give more credit to information that is ideologically congruent. Typical designs to measure these asymmetries select, often arbitrarily, a small set of news items as experimental stimuli without clear reference to a "population of information." This pre-registered study takes an alternative approach by, first, conceptualizing estimands in relation to all political news. Second, to represent this target population, it uses a set of 80 randomly sampled items from a large collection of articles from Google News and three fact-checking sites. In a subsequent survey, a quota sample of US participants (n = 1,393) indicate whether they believe the news items to be true. Conservatives are less truth-discerning than liberals, but also less affected by the congruence of news.