Social Media, Cognitive Reflection, and Conspiracy Beliefs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A growing number of Americans stay informed about current events through social media. But using social media as a source of news is associated with increased likelihood of being misinformed about important topics, such as COVID-19. The two most popular platforms—Facebook and YouTube—remain relatively understudied in comparison to Twitter, which tends to be used by elites, but less than a quarter of the American public. In this brief research report, we investigate how cognitive reflection can mitigate the potential effects of using Facebook, YouTube and Twitter for news on subsequent conspiracy theory endorsement. To do that, we rely on an original dataset of 1,009 survey responses collected during the first wave of the coronavirus pandemic in the United States, on March 31, 2020. We find that using Facebook and YouTube for news increases conspiracy belief (both general and COVID-19 specific), controlling for cognitive reflection, traditional news media use, use of web-based news media, partisanship, education, age, and income. We also find that the impact of Facebook use on conspiracy belief is moderated by cognitive reflection. Facebook use increases conspiracy belief among those with low cognitive reflection but has no effect among those with moderate levels of cognitive reflection. It might even decrease conspiracy belief among those with the highest levels of cognitive reflection.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it