"Social Media, Social Networks, and Social Movements: Emerging Research Challenges"
Bibliographic record
Abstract
Social media has been employed from Egypt’s uprising to global climate change movement and India’s violence against women’s movement to Occupy Wall Street. These large sustained protests have used social media in ways that goes beyond simple communications. Social media are Web 2.0 technologies that allow people to produce and share user generated content (O’Reilly, 2007; Shirky, 2009). Digital media enable a certain set of affordances that make various uses of these technologies possible (Bharati et al, 2014). The digital media affordances, available to both collective and individual actors, translate into capabilities afforded to social movements (Tufecki, 2014). The role of these digital media technologies in collective action has to be studied and the actual mechanisms uncovered. Commenting on the role of social media in Egypt’s uprising a leader of the movement stated that
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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 | 0.018 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.008 | 0.023 |
| Scholarly communication | 0.016 | 0.040 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 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".