Social learning and partisan bias in the interpretation of climate trends.

ABSTRACT: Vital scientific communications are frequently misinterpreted by the lay public as a result of motivated reasoning, where people misconstrue data to fit their political and psychological biases. In the case of climate change, some people have been found to systematically misinterpret climate data in ways that conflict with the intended message of climate scientists. While prior studies have attempted to reduce motivated reasoning through bipartisan communication networks, these networks have also been found to exacerbate bias. Popular theories hold that bipartisan networks amplify bias by exposing people to opposing beliefs. These theories are in tension with collective intelligence research, which shows that exchanging beliefs in social networks can facilitate social learning, thereby imp

SUBMITTER: Guilbeault D 

PROVIDER: S-EPMC6166837 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature