Role of Problematic Internet Use, Sense of Belonging and Social Appearance Anxiety in Facebook Use Intensity of University Students
Bibliographic record
Abstract
The aim of this study was to examine the role of problematic internet usa, sense of belonging and social appearance anxiety in facebook use intensity of university students. The sample of the study consisted of 484 (332 female, 68.6% and 152 male 31.4%) different faculties of various universities of Konya. Problematic Internet Use Scale, General Belongingness Scale, Facebook Intensity Scale, The Social Appearance Anxiety Scale, Personal Knowledge Form were used in the study. Pearson Correlation Product Conduct and multiple regression analysis were used to analyze the data. According to the findings of the study, There was a significant positive relationship between the mean scores of the participants on the Facebook Intensity Scale and the mean scores of the Problematic Internet Use Scale and the Social Appearance Anxiety Scale. Regression analysis examined shows that social appearance anxiety and problematic internet use and general belonging sense average scale scores were significantly prediction of Facebook İntensity Scale Scores. The results of the research were discussed within the framework of the literature. Based on the findings of the research, comments and suggestions were developed.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".