Abstract
We compare two alternative measures for assessing people’s emotional reactions to political stimuli: the traditional self-report measure and facial expression analysis. We recruited participants to take part in a study examining reactions to a set of negative political commercials aired during the 2018 elections. We compare people’s self-reporting of their emotional reactions to negative political advertisements with their expressed emotion, according to the facial expression analysis. We find the discriminant validity of the facial expression analysis is higher than the self-report measure. Second, the self-report and facial expression measures of emotion have little convergent validity: we fail to find a consistent and strong positive correlation between the self-report and facial software measures of the same emotion and the same political advertisement. Third, the facial software measure has better predictive validity than the self-report measure, generating better predictions for the three dependent variables examined: changes in political interest, changes in people’s confidence in elected officials, and people’s assessment of the tone of the senate campaign.
Get full access to this article
View all access options for this article.
References
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
