War stories in social media: Personal experience of Russia-Ukraine war
Bibliographic record
Abstract
In light of the current Russia-Ukraine war, traumatic stress in civilian Ukrainians is a critical issue for psychological science to examine. Social media is often viewed as a tribune for authors’ self-expressing and sharing stories on the war’s impact upon their lives. To date, little is known about how the civilians articulate their own war experience in social media and how this media affects the processing of traumatic experience and releasing the traumatic stress. Thus, the goal of the study is to examine how the personal experience of the Russia-Ukraine war 2022 is narrated on Facebook as a popular social media venue. The study uses a corpus of 316 written testimonies collected on Facebook from witnesses of the Russia-Ukraine war and compares it against a reference corpus of 100 literary prosaic texts in Ukrainian. We analyzed both corpora using the Ukrainian version of the Linguistic Inquiry and Word Count software – LIWC 2015 (Pennebaker et al., 2015). We identified psychological and linguistic categories that characterized the war narratives and distinguished it from the literary reference corpus. For instance, we found the style of Facebook testimonies to be significantly less narrative and more analytic compared to literary writings. Therefore, writers in the social media focus more on cognitive reappraisal of the tragic events, i.e., a strategy known to lead to a reduction of stress and trauma. Disclosure Statement No potential conflict of interest was reported by the authors.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".