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An extensive literature examines how partisanship divides public opinion on hot-button political issues, but little is known about its potential to polarize attitudes on bipartisan issues. Recent work shows that while Americans hold strong preferences for bipartisanship, their attitudes toward bipartisan issues quickly become polarized when associated with partisan identities. While prior research has examined the effect of these associations in lab settings, tests outside the lab are far more rare. In this research note, we aim to provide such a test by leveraging a bipartisan issue that became associated with partisan identities suddenly in 2018: the presidential alert. While the presidential alert—a product of bipartisan efforts to improve the government's capacity to send emergency communications in the wake of Hurricane Katrina—received little notice when signed into law, it gained widespread media attention during its inaugural test in 2018. We rapidly recruited a sample of US adults immediately before the alert was sent, such that participants in our study received the alert on their phones while completing a survey. We exploited the timing of the alert to randomize whether respondents answered questions about the alert moments before or after receiving it. Across two experiments we find little evidence that associating the alert with the Trump administration had any polarizing effect on attitudes, even when explicitly associated with a partisan cue, suggesting that at least some bipartisan attitudes are not as easily polarized as prior work implies.

AbstractA large literature demonstrates that conservatives have greater needs for certainty than liberals. This suggests an asymmetry hypothesis: Conservatives are less open to new information that conflicts with their political identity and, in turn, political accountability will be lower on the right than the left. However, recent work suggests that liberals and conservatives are equally prone to politically motivated reasoning (PMR). The present article confronts this puzzle. First, we identify significant limitations of extant studies evaluating the asymmetry hypothesis and deploy two national survey experiments to address them. Second, we provide the first direct test of the key theoretical claim underpinning the asymmetry hypothesis: epistemic needs for certainty promote PMR. We find little evidence for the asymmetry hypothesis. Importantly, however, we also find no evidence that epistemic needs promote PMR. That is, although conservatives report greater needs for certainty than liberals, these needs are not a major source of political bias.

ABSTRACTLarge numbers permeate political life, and students of political science can expect to encounter a wide range of numbers in newspaper articles, course readings, and statistics. Recent research in cognitive psychology demonstrates that American adults make systematic errors when comparing numbers in the millions, billions, and trillions. Political decisions made by voters often require weighing large quantities that range across many orders of magnitude, which is difficult without at least a basic understanding of relative magnitudes. If students also lack an understanding of large numbers, professors cannot meaningfully teach them about political phenomena involving such magnitudes. The authors designed and tested an exercise to improve students' accuracy in dealing with large magnitudes, which had immediate and sustained effects on their political judgments about information involving large numbers.

Online surveys, particularly those that draw samples from online panels of experienced respondents, now comprise a large segment of the academic and commercial opinion research markets due to their low cost and flexibility. A growing literature examines the implications of online surveys for data quality, most commonly by comparing demographic and political characteristics of different samples. In this paper, we explore the possibility that personality may differentially influence the likelihood of participation in online and face-to-face surveys. We argue that individuals high in extraversion and openness to experience may be underrepresented, and those low in these traits overrepresented, in professionalized online panels given the solitary nature of repeated survey-taking. Since openness to experience in particular is associated with liberal policy positions, differences in this trait may bias estimates of public opinion derived from professionalized online panels. Using data from the 2012 and 2016 dual-mode American National Election Studies, we compare political preferences and personality traits across parallel face-to-face and online samples. Respondents in the online samples were, on average, less open to experience and more politically conservative on a variety of issues compared to their face-to-face counterparts. This was true especially in 2012, when online respondents were drawn from a large panel of experienced respondents. We also find openness to be negatively related to the number of surveys completed by these respondents. These results suggest that reliance on professionalized survey respondents, who comprise the vast majority of online survey samples, can bias estimates of many quantities of interest.

There is widespread concern that Russia and other countries have launched social-media campaigns designed to increase political divisions in the United States. Though a growing number of studies analyze the strategy of such campaigns, it is not yet known how these efforts shaped the political attitudes and behaviors of Americans. We study this question using longitudinal data that describe the attitudes and online behaviors of 1,239 Republican and Democratic Twitter users from late 2017 merged with nonpublic data about the Russian Internet Research Agency (IRA) from Twitter. Using Bayesian regression tree models, we find no evidence that interaction with IRA accounts substantially impacted 6 distinctive measures of political attitudes and behaviors over a 1-mo period. We also find that interaction with IRA accounts were most common among respondents with strong ideological homophily within their Twitter network, high interest in politics, and high frequency of Twitter usage. Together, these findings suggest that Russian trolls might have failed to sow discord because they mostly interacted with those who were already highly polarized. We conclude by discussing several important limitations of our study—especially our inability to determine whether IRA accounts influenced the 2016 presidential election—as well as its implications for future research on social media influence campaigns, political polarization, and computational social science.

There is widespread concern that Russia and other countries have launched social-media campaigns designed to increase political divisions in the United States. Though a growing number of studies analyze the strategy of such campaigns, it is not yet known how these efforts shaped the political attitudes and behaviors of Americans. We study this question using longitudinal data that describe the attitudes and online behaviors of 1,239 Republican and Democratic Twitter users from late 2017 merged with nonpublic data about the Russian Internet Research Agency (IRA) from Twitter. Using Bayesian regression tree models, we find no evidence that interaction with IRA accounts substantially impacted 6 distinctive measures of political attitudes and behaviors over a 1-mo period. We also find that interaction with IRA accounts were most common among respondents with strong ideological homophily within their Twitter network, high interest in politics, and high frequency of Twitter usage. Together, these findings suggest that Russian trolls might have failed to sow discord because they mostly interacted with those who were already highly polarized. We conclude by discussing several important limitations of our study—especially our inability to determine whether IRA accounts influenced the 2016 presidential election—as well as its implications for future research on social media influence campaigns, political polarization, and computational social science.

In this study, we contribute to the personalized medicine and health care management literature by developing and testing a new participative design approach. We propose that involving gastroenterologists in the development of a predictive test to assist them in their clinical decision-making process for the treatment of inflammatory bowel diseases will increase the likelihood of their acceptance of the innovation. Based on data obtained from 6 focus groups across Canada from a total of 28 physicians, analyses reveal that current tools do not enable discriminating between treatment options to find the best fit for each patient. Physicians expect a new predictive tool to have the capability of showing clear reliability and significant benefits for the patient, while being accessible in a timely manner that facilitates clinical decisions. Physicians also insist on their key role in the implementation process, hence confirming the relevance and importance of participative designs in personalized medicine.