The Arctic Twittersphere and the Russian Invasion of Ukraine
Bibliographic record
Abstract
Social media use has grown in popularity in recent years, becoming a primary source of information for many. Several scholarly inquiries have analyzed how the Arctic region has been portrayed in traditional media. However, no study has comprehensively detailed how the region has been presented on social media. The objective of this article is to sketch the contours of the Arctic discussion on Twitter and to inquire whether significant geopolitical events impact the nature of the online discussion. Using tweets on Arctic issues published between January 2020 and August 2022, we assessed the timing, prevalence, and nature of messages about the circumpolar North. Overall, the Arctic conversation on Twitter is first and foremost an Arctic climate conversation, focusing on climate change, Arctic sea ice, and permafrost thawing. Climate issues are the most salient ones and are treated independently from other topics by online users. We assessed whether the Russian invasion of Ukraine changed this dominance. We found that the Arctic Twittersphere remained still predominantly focused on climate issues, although the invasion increased Arctic military security discussions dissociated from other diplomatic or natural-resources considerations.
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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 | 0.000 |
| 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 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".