12:00 pm - 1:00 pm EST
Virtual – Registration Required
Part of the Speaker Series on Misinformation, co-sponsored by the NULab at Northeastern University.
Shanto Iyengar is the William Robertson Coe Professor of American Studies at Stanford University. He has served as Co-Principal Investigator of the American National Election Study since 2014. His areas of interest include party polarization and mass communication. He is the author or co-author of Media Politics: A Citizen’s Guide (Norton, 2015); News That Matters (University of Chicago Press, 1987, 2010), Is Anyone Responsible? (University of Chicago Press, 1991), Explorations in Political Psychology (Duke University Press, 1995), and Going Negative (Free Press, 1995).
Registration for this event has closed, a recording is available here.
There are competing accounts for the partisan divisions occurring throughout American life. One is that they are genuine divides due to a strengthened sense of partisan identity. The other is that they reflect partisan cheerleading—insincere support for the “home team” when there is little cost to doing so. We assess the applicability of these claims to political misinformation in the post-Trump era. We test between these alternatives with experiments that offer incentives for correct survey responses and allow respondents to search for information before answering each question. We find that partisan cheerleading inflates informational divides modestly and incentives have no impact on partisan divides in information search.
In a follow-up study, we apply this research design to investigate beliefs about the COVID-19 pandemic. We find that partisan factual disagreements on COVID-19 resemble those on other political issues. Contrary to the cheerleading account, the level of disagreement is unaffected when we impose a financial cost for knowingly providing incorrect answers. We further find only weak evidence that the health risks posed by the pandemic attenuate these divides. While partisan differences in factual knowledge become smaller among people who express personal concern about becoming infected, partisan divides are larger among the elderly, a group especially at risk.
Overall, our findings suggest that partisan motivated reasoning guides factual beliefs about a major public health crisis just as much as beliefs about less personally consequential issues. This result is surprising in that partisanship appears to override information processing based on the protection of personal well-being, even survival.