Keeping it peaceful: Twitter and the Gezi Park movement
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
Over the last decade, social media platforms have become the leading communication tools for activists and protesters all over the world. Understanding protesters’ motivations and reasons for using social media is a challenging issue for researchers. In this article, we analyzed the use of Twitter during the anti-governmental protests in Istanbul that was launched in May 2013. We examined 13,794 tweets posted to the #direngeziparki hashtag over a 6-day period. Based on the results of a qualitative content coding of the tweets, we found that the Twitter platform was widely used to mobilize protesters, share information about the events, and express opinions about the policing of the protests. We argue that social media can help keep protests peaceful by preventing vandalism, informing the protesters about extremist or violent groups participating in the protests, and can help them to avoid engaging in violent acts against police forces.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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