Recent Development and Emerging Trends of Research on Rohingya Refugee Crisis (1993-2020): A Bibliometric Analysis
Bibliographic record
Abstract
Rohingya refugees are one of the top displaced communities in the world. Refugee crises have been a global concern in recent times, involving inclusive research. This bibliometric analysis aims to produce an overview of Rohingya refugees and help researchers build intuitions on them. To this end, the author implements a bibliometric analysis using VOSviewer and Biblioshiny software for cluster analysis and three-factor analysis using publications from Scopus and Web of Science. The author uses180 WoS and 202 Scopus documents to analyse the data based on inclusion criteria. The study results indicate sharp increasing trends of publications and citations in recent times after the major influx in 2017. Bangladesh, the USA, and Australia made the highest number of publications and collaborations on Rohingya refugee research. Besides, the study results visually demonstrate the sub-areas linking with the Rohingya refugees concerning the scientific journals, leading areas, major influencing countries, authors, sources, institutions, and exciting research directions. The study also identifies the research collaborations between countries and authors. Finally, based on keywords and three-field analyses, it is concluded that Rohingya, refugees, Bangladesh, Myanmar, Rohingya refugees, mental health, and forced migration have captivated extensive attention by the researchers on Rohingya refugees in the last three years.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.052 | 0.034 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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, 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".