Social Media and COVID-19: A Mixed-Methods Analysis to Document Canadian Adults’ Perceptions of the Positive and Negative Sides of Their Social Media Use
Bibliographic record
Abstract
Using a mixed-methods approach, the purpose of this study was to document some Canadian adults’ social media experiences during the COVID-19 pandemic to understand potential changes in motives and attitudes related to social media. Participants (n = 68; 17 - 66 years old) completed an online survey with open-ended and Likert-scale questions between April 25 and June 12, 2020. Qualitative responses were coded and analyzed for themes related to the positive and negative aspects of social media use and changes in attitudes. Descriptive statistics, ANOVAs, and t-tests were run to assess perceived changes in frequency and motivations driving social media use, in addition to the perceived utility of social media. Participants perceived increases in their social media use, particularly to meet socialization and entertainment needs. During the pandemic, participants valued social media for its opportunity to maintain connections, but also expressed concerns about how much they were using it and their exposure to negative information. The results suggest that maximizing the potential of social media to maintain or increase connections may be beneficial for the well-being of some Canadians in early and middle adulthood during unprecedented times of physical distancing.
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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 | 0.019 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".