Research Note—Why Following Friends Can Hurt You: An Exploratory Investigation of the Effects of Envy on Social Networking Sites among College-Age Users
Bibliographic record
Abstract
Research findings on how participation in social networking sites (SNSs) affects users’ subjective well-being are equivocal. Some studies suggest a positive impact of SNSs on users’ life satisfaction and mood, whereas others report undesirable consequences such as depressive symptoms and anxiety. However, whereas the factors behind the positive effects have received significant scholarly attention, little is known about the mechanisms that underlie the unfavorable consequences. To fill this gap, this study uses social comparison theory and the responses of 1,193 college-age Facebook users to investigate the role of envy in the SNS context as a potential contributor to those undesirable outcomes. Arising in response to social information consumption, envy is shown to be associated with reduced cognitive and affective well-being as well as increased reactive self-enhancement. These preliminary findings contribute to the growing body of information systems research investigating the dysfunctional consequences of information technology adoption in general and social media participation in particular.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".