The Icing On The Cake: How Social Media Constructs A Fourth Personality Layer
Bibliographic record
Abstract
This article presents a critical literature review of the relationship between social media use and thedevelopment of personality disorder features, particularly among young people. Drawing on psychologicaltheory, psychological study, developmental research, and Marshall McLuhan’s famous probe “The medium isthe message” (McLuhan, 1964, p. 7), this review examines key findings across disciplines while offeringinterpretive insights into emerging behavioral patterns. A large body of data now shows a stark rise inindividuals aged 12-25 experiencing mental health issues, including depression, anxiety, suicidality,hospitalizations, and chronic low self-esteem. While these symptoms have been widely discussed, this paperexplores the deeper structural implications of these outcomes—specifically, how long-term social media usemay be shaping identity and contributing to the emergence of Cluster B personality traits, including borderlineand histrionic features, affecting relationships, real-life problems (finding joy, goal setting for the future,employment), and simply “growing up”. Synthesizing studies on self-image, child development, personalitydisorders, and influencer culture, this review highlights a critical gap in current discourse: not just what ishappening to mental health, but why, and the collateral damages of the ripple effects. This review connectsestablished psychological theories to patterns of online behavior, proposing that the medium itself (socialmedia) may be rewiring the developing brain, contributing to a newly dominant FPL or “fourth personalitylayer”—a digital self that increasingly dictates offline thought, behavior, and sense of identity. This reviewcontributes to a deeper understanding of how social media may not just reflect who we are, but activelyconstruct who we become.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".