Social Media among Thai students: Narcissism, self-identity or empowerment?
Bibliographic record
Abstract
Background: Social media has now become a ubiquitous part of everyday life, especially for young people. This technology is a double-edged sword and can be used to empower or isolate users. This research is designed to enhance our understanding of how social media is being used by young people, how it affects them and their attitudes towards it. Results: This paper reports on the findings of a follow-up study to explore student feelings and attitudes and student preferences and self-perceptions when using technology. Earlier research examined emerging trends and changes in how students and staff use technology for learning and teaching and ownership of technology. This part of the long-term research project explored student attitudes and self-perceptions when using social media for personal use. Findings confirmed that there is a high use of Facebook amongst the young people in this study and their attitudes toward social media are more positive than negative. Participants felt that social media helped them to communicate with people from around the world, was easy to use for communication and could be used anywhere and at any time. They used social media most often to communicate with friends, colleagues, family and significant others, rather than people they did not know personally. However, they did use social media to build an online presence or profile and used this online platform to raise their status and for self-promotion to the wider community. Participants also admitted that social media impaired concentration, listening and completing activities in the classroom and sometimes caused personal relationship problems. A mobile phone is the device they use most often to access social media. Results also indicate that young people using social media in Thailand do not have a high level of concern about third-party access to their data. However, results from the study do not clearly show that using social media affects the ability of young people to communicate face-to-face. Conclusion: The widespread use of Facebook amongst the Thai students taking part in this study was found to have both positive and negative effects on their communication, entertainment, academic and social lives, their sense of self and personal empowerment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".