The Effect of Loneliness on Social Networking Sites Use and Its Related Behaviors
Bibliographic record
Abstract
INTRODUCTION: The current research was conducted to examine the effect of "Loneliness", on time spent in Social Networking Sites (S.N.S), main reasons for S.N.S use, and its related behaviors. MATERIALS & METHODS: 156 students of Shiraz University voluntarily participated in this research. Loneliness was assessed usingthe UCLA Loneliness scale. 25% of highest scoring students reported that they were lonely whereas 25% of the lowest scoring students were considered to be non-lonely. The positive and negative reasons of using S.N.S were assessed based on Reasons for Internet Use Scale, and internet behaviors were assessed based on Scale of Internet Behaviors. RESULTS: There was no difference in time spent in S.N.S as well as the positive and negative reasons of using S.N.S (contrary to literature), but internet behaviors showed a significant difference between "lonely" and "non-lonely" individuals. "Lonely" and "non-lonely" individuals showed a significant difference in "social aspect" of S.N.S behaviors. There was also a significant difference between "Lonely" and "non-Lonely" individuals in "Negative impact" of S.N.S behaviors. Yet, there seemed to be no difference in "competency and convenience aspect" of S.N.S behaviors. CONCLUSIONS: This study suggested that there is no difference between lonely and non-lonely individuals in reasons for using S.N.S and time spent in S.N.S. This finding stands contrary to previous research findings and general literature on the subject In other words, what drives people to S.N.S at the first place shows no significant difference between lonely and non-lonely individuals while after attending S.N.S, social behavior of lonely individuals shows a significant difference which is consistently enhanced online. Lonely people also significantly develop internet-related problems in their daily functioning, including interference with real life socializing.
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".