How Do Young Adults Feel About Receiving “Likes” on Social Media? The Moderating Role of Shyness and Cybervictimization
Bibliographic record
Abstract
The current study explored the emotional effects on individuals of receiving fewer “Likes” than others on social media, as well as the potential moderating roles of participant shyness and previous experiences with cybervictimization. Participants were 1,007 undergraduate students (751 women; M age = 19.33 years, SD = 7.2 years) from a university in Eastern Ontario, Canada. During a standardized social media task, participants were randomly assigned to receive either “few Likes,” “some Likes,” or “many Likes.” They completed self-report measures (e.g., self-esteem, sense of life meaning, emotions, loneliness, and intentions to limit social media use) both before and after the experimental task. Among the results, participants who received fewer likes reported significantly lower levels of self-esteem, reduced feelings of meaningful existence, and fewer positive emotions. Additionally, the negative impact of insufficient positive social media feedback was more pronounced among emerging adults who reported being more shy and had previously experienced cybervictimization. Our findings shed light on the potential detrimental outcomes associated with social media use among young adults.
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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 | 0.001 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".