Bibliographic record
Abstract
The purpose of the study is to conduct a bibliometric analysis of psychological publications devoted to the phenomenon of beauty. The research material (2214 articles) was extracted from the Scopus bibliographic database. The VOSviewer and biblioshiny software tools were used to analyze the results and build a bibliometric map. The construction of a conceptual map made it possible to identify four clusters related to the study of beauty: (1) the bodily component of a person; (2) attractiveness; (3) aesthetic phenomena; and (4) sociocultural processes. Thematic clustering using the Walktrap algorithm identified four themes; with the theme with the highest density and centrality devoted to the study of attractiveness, in particular, physical attractiveness and facial attractiveness. Five countries (USA, UK, Germany, Canada, Australia) produced almost 3/4 of the total number of publications (74.2%). The contribution of Russian authors amounted to 17 articles (0.8%). Trend analysis shows that in recent years there has been a growing interest in social media, aesthetic emotions and values. It is concluded that the main phenomena that are associated with the concept of “beauty” and are studied in psychology are body image, attractiveness, physical attractiveness, facial attractiveness and aesthetics. The conducted analysis shows that beauty as a value, remaining an understudied category, is explored in the context of positive psychology.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.043 | 0.064 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; both teacher heads agree on what is shown here.
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".