Bibliometric Analysis of Tourism and Community Participation Research: A Comparison of Scopus and Web of Science Databases
Bibliographic record
Abstract
This study aims to provide a bibliometric analysis of tourism and community participation based on the Scopus and WOS databases.As studies on community participation have developed in the last decade, it is important to map and compare research progress on community participation.This study uses the two most popular databases to analyze and provide an overview of the scope of overlap and singularity databases and the popularity of documents and authors in the two databases.Data collection was carried out from May 23 to 25, 2022.Therefore, 457 and 350 documents from Scopus and WOS were compared using bibliometric analysis to determine growth, overlap, prolific and influential author, most cited document and keywords, as well as productivity of country and institutions.The data collected were analyzed using Excel and VOSViewers applications.The results showed that the growth trend of tourism and community participation research continues to increase in both databases.However, Scopus has a broader scope in tourism and community participation fields and more unique documents.Wall G and Tosun C are the most prolific and influential authors, while China is the most productive country.Developing countries significantly contribute to international publications related to tourism and community participation.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.033 | 0.021 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".