Comprehensive Bibliometric Analysis of Commercial Recreation Research: WoS Database Example (1986 - 2023)
Bibliographic record
Abstract
This study was carried out to reveal the structure of change and development by conducting a comprehensive research in the international literature on the subject of “commercial recreation” research. The dataset, which includes analytical data of academic articles on commercial recreation research reflected in the international literature for the years 1986-2023, was downloaded from the WoS database within the framework of the determined academic actors. The relevant data set was tested and analyzed in VOSviewer and Bibliometrix R Statistical Analysis Program. As a result of the performance analysis conducted on research, it was determined that the most academic articles were contributed to the international literature in the "English" language, in the year "2023", in the research fields of "Environmental Sciences Ecology" and in the "Science Citation Index Expanded (SCI-EXPANDED)" scanned index. In order to reveal the comprehensive social structure of the “commercial recreation” literature, tests were conducted on the analysis of authors, universities and countries in the context of co-authorship. In order to reveal the comprehensive conceptual structure of the relevant research topic, tests regarding keyword analysis were carried out in the context of common words. As a result of the tests and analyses; “Tyrvainen, L.” was found to be in the first place in terms of the number of articles and total link strength value, and “Cox, S.” was found to be in the first place in terms of the number of citations. It was determined that “Noaa” ranked first in terms of article, “Univ Calgary” ranked first in terms of citation count, and “Queensland Univ Technol” ranked first in terms of total link strength value. It has been determined that “USA” ranks first in terms of article, citation and total link power value. Within the scope of keywords; “management”, “recreation”, “conservation” were found to be in the first place in terms of usage numbers, and “management”, “conservation”, “perceptions” were found to be in the first place in terms of total connection strength values. It has been determined that the words “recreation”, “management” and “urban” are in the first place in terms of the number of uses in the titles of the relevant articles, and “commercial”, “recreation” and “management” are in the first place in terms of the number of uses in their summaries.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.055 | 0.043 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".