Perceptions and Concerns About Misinformation on Facebook in Canada, France, the US, and the UK
Bibliographic record
Abstract
Abstract Across the globe, people are concerned about misinformation despite evidence suggesting actual exposure is limited and specific to subgroups. We examine the extent to which concerns about misinformation on Facebook are related to perceived exposure to misinformation on the platform (misinformation perceptions), political experiences on Facebook, and country context. Using survey data gathered in February 2021 in four countries (Canada, France, UK, and the US), we find a strong positive correlation between perceptions of and concerns about misinformation on Facebook. We explain that this concern about misinformation is rational in that it is rooted in personal experience of perceived exposure. Seeing political content and observing uncivil political discussions on Facebook also relate to concerns about misinformation. We explain heightened concerns about misinformation in terms of views about the virality of misinformation on Facebook as well as the presumed influence of misinformation on others (third-person effects), which makes misinformation a perceived threat to democracy and society. The observed relationships are supported in three of the four countries, but France tends to be an exception. Understanding citizens’ concerns about misinformation is important for understanding support for interventions, including platform regulation.
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How this classification was reachedexpand
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".