The Role of Social Media in Enhancing Communication among Individuals: Prospects and Problems
Bibliographic record
Abstract
This study is a discussion about the role that social media plays in enhancing communication among individuals, highlighting its prospects and related challenges. This research examines the impact of social media on improving communication among individuals and its prospects and challenges. This study had taken an integrated approach of secondary data analysis methodology through an extensive systematic review of the existing literature, along with the Canadian Research Data Collection (CREDC) national web-survey, to collect the attitudinal and behavioral insight of social media users on different platforms like Facebook, Twitter, and LinkedIn considering theoretical frameworks like Social Presence Theory and Media Richness Theory. Further, this conceptual review used PRISMA guidelines to examine how social media improves communication. Eligibility and exclusion criteria ensured peer-reviewed article selection and credibility. Study reveals that social media platforms significantly enhance interpersonal communication by fostering increased interconnectedness, more accessible information, and community formation. Notably, while these digital environments have considerable benefits, such as the facilitation of learning and support networks, they are also fraught with challenges, including misinformation, privacy concerns, and potential adverse effects on mental health. These findings therefore have dual approaches to reaping the benefits of social media in communication: the promotion of user education to reduce misinformation and building up digital literacy, while there is also a need to consider regulations that will protect against violation of privacy and cyberbullying. It is at this point that stakeholders will, arguably, have fewer difficulties in making use of social media to continue developing active citizenship and rich interpersonal relationships. Future research is encouraged to further explore the implications of emerging technologies on social media communication practices.
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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 | 0.041 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.013 | 0.024 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".