From virtual space to public space: The role of online political activism in protest participation during the Arab Spring
Bibliographic record
Abstract
This study examines the relationship between online social media use and protest participation during the Arab Spring, pro-democracy movements that swept across vast parts of the Middle East and North Africa (MENA). What role did online communication media play in individual decisions to participate in these high-risk political activities? We address this question by drawing on microdata from the Arab Barometer Wave III (2012–2014), a large cross-national survey of citizens nested in administrative divisions across a dozen Muslim-majority countries. Using hierarchical linear modeling, we investigate the multilevel associations between online activities and the likelihood of getting involved in anti-government protests. Adjusting for individual- and regional-level confounders, as well as country fixed effects, we find that online political activism specifically, rather than Internet and social media use in general, is associated with higher odds of protest involvement during the Arab uprisings. In addition, we find that the positive linkage between individual online activism and protest is weaker in communities with a higher proportion of politically cyberactive residents.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".