Measuring Continued Influence of Corrected Political Misinformation
Misinformation is an ever more pressing issue in our society. An important question to look at on the topic of misinformation is what the underlying mechanism is by
which misinformation affect judgments about its targets, and the degree to which “fact checks” designed to
correct such misinformation, are capable of reversing these effects. Answering this question is critical for
developing effective countermeasures to reduce misinformation’s impact on social media users. This is the idea that we tested,
namely that misinformation negatively impacts affective evaluations of its targets, and that these effects
persist even when a correction has been provided and is explicitly remembered.
(Thomas Hogeboom, Michael S. Cohen, Victoria Halewicz, Joseph W. Kable)
• How does misinformation affect judgments about politicians?
• To what degree do “fact checks” designed to correct such misinformation reverse these effects?
Hi Thomas, Ouch! What an…
Ouch! What an important (and disturbing) finding! It's easy to see how this phenomenon can be weaponized by unscrupulous political candidates who want to smear their opponents with outrageous (and false) accusations. Indeed, it clearly already has been. How many people still believe that various democratic leaders are guilty of child sex trafficking? Your results suggest that truth doesn't matter. Once the (emotionally salient, disturbing) accusation is out there, the damage is already done, even if it's an outrageous lie.
This raises really interesting questions about whether the nature of the accusation matters - one can imagine exploring the various salient features to see which sorts of accusations "stick" most perniciously. (Careful with that though, we don't want to give the unscrupulous folks any better ammunition.) I hope that your research will eventually illuminate the best way to "unstick" false accusations in the public's mind.
I'm curious to know whether…
I'm curious to know whether you have tried to develop ideas on how corrections might be made to be more effective. You might consider relating some of your findings to research in statistical learning, which appear in the vision research and perception science literatures, which show that learning low variance distributions when starting out with a high variance distribution takes longer than the reverse. I'll dig up a reference or two on this... I know that Konrad Koerding, also on faculty here, has done some work on this topic.
these are powerful findings. Did you see any effect of gender or age? These could be interesting factors.