It’s Fine If Others Do It Too: Privacy Concerns, Social Influence, and Political Expression on Facebook in Canada, France, Germany, the United Kingdom, and the United States
Bibliographic record
Abstract
Political expression is a focal point for understanding how digital media have transformed political engagement. Privacy concerns tend to impede online political expression, but this relationship is still poorly understood. Based on the theory of reasoned action, this study focuses on the role of social influence and institutional privacy concerns in political expression on Facebook. We draw on research on the privacy calculus to examine how observing the behavior of Facebook friends moderates the relationship between privacy concerns and online political expression. We use survey data gathered in 2023 from Canada, France, Germany, the United Kingdom, and the United States ( n = 5,936). Across all five countries, we find that observing Facebook friends posting political content bolsters political expression on Facebook, as per our preregistered analysis. In all countries except Germany, privacy concerns impede political expression on Facebook. Also, the importance of institutional privacy concerns for political expression depends on the observed posting behavior of Facebook friends. This moderated effect is only observed in three of the five examined countries, however. Our findings offer new insights into the factors that encourage and discourse political expression, particularly on Facebook which is a platform that has been widely criticized for failing to protect its users’ privacy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".