You Want to go where? Shifts in social media behaviour during the COVID-19 pandemic
Bibliographic record
Abstract
COVID-19 restrictions have transformed acceptable sociability, shifting behaviours toward technology-facilitated interactions as a substitute for face-to-face connectivity. Virtual communities are increasingly important forums to share leisure travel experiences while travel itself remains severely disrupted. Pre-pandemic posting about travel built social capital, reflecting values that were generally pro-tourism. However, instances of “shaming’ those continuing to travel during COVID-19 have devalued tourism’s social currency. To understand the impact of COVID-19 on travel-related self-disclosure patterns, the study analysed data from Canada’s destination marketing organization’s Instagram page over two peaks and one valley of the pandemic, uncovering several behaviours, including expressions of sentiment, popular for their simplicity and minimal risk, and affective advocacy, a riskier other-focused behaviour. From first peak to second, the use of self-focused behaviours went up, whereas the use of other-focused behaviours went down. The findings show how social calculus impacts patterns of self-disclosure, reshaping digital interactions associated with leisure.
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.
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 | 0.017 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".