Recognizing Fake News: Experimentally Assessing Competing Explanations

• In Event: Biased Perceptions and their Influence on Opinion

Abstract

Deliberately misleading and/or satirical news stories have the problematic potential to misinform voters. However, while observational studies have sought to quantify the impact of these stories, we know little about how susceptible individual voters are in falling for these stories, and particularly how this susceptibility may vary across different news stories. In order to test this, we develop a conjoint experiment that varies articles' source publication, headlines, social me dia platform, photo, and partisan slant to assess how easily voters are able to detect both misleading and satirical news stories. Along with the substantive conclusions arising from this experiment, we also make several methodological points regarding the randomization of conjoints and how particular probabilities of certain factor levels may complicate the interpretation of results by altering respondents' perceptions of the proper base rate of a given factor level.

Authors

• Douglas Ahler, Florida State University

• Stephen N Goggin, San Diego State University