Datasets and methods across research fields
In the 30-day window 2026-10-07 – 2026-11-05 (30 days), 637 of 4,746 unique papers (13.4%) name a watched dataset and 2,025 (42.7%) name a watched equation or method.
These are observed name matches in this site’s selected journals, not adoption rates for an entire field. A named method may be discussed or compared rather than used. More searchable text increases the chance of a match. The snapshot measures one window; it does not establish a time trend or explain differences between fields.
| Journal field | Papers | Dataset names | Method names | Both | Abstract available | Full text available |
|---|---|---|---|---|---|---|
| Finance | 447 | 95 / 447 (21.3%) | 203 / 447 (45.4%) | 68 / 447 (15.2%) | 158 / 447 (35.3%) | 91 / 447 (20.4%) |
| Accounting | 37 | 1 / 37 (2.7%) | 12 / 37 (32.4%) | 0 / 37 (0.0%) | 9 / 37 (24.3%) | 5 / 37 (13.5%) |
| Economics | 898 | 179 / 898 (19.9%) | 394 / 898 (43.9%) | 141 / 898 (15.7%) | 337 / 898 (37.5%) | 281 / 898 (31.3%) |
| Health Economics and Policy | 320 | 36 / 320 (11.2%) | 105 / 320 (32.8%) | 22 / 320 (6.9%) | 246 / 320 (76.9%) | 110 / 320 (34.4%) |
| Management | 371 | 58 / 371 (15.6%) | 131 / 371 (35.3%) | 41 / 371 (11.1%) | 188 / 371 (50.7%) | 126 / 371 (34.0%) |
| Marketing | 121 | 17 / 121 (14.0%) | 46 / 121 (38.0%) | 13 / 121 (10.7%) | 42 / 121 (34.7%) | 32 / 121 (26.4%) |
| Information Systems | 223 | 32 / 223 (14.3%) | 68 / 223 (30.5%) | 17 / 223 (7.6%) | 93 / 223 (41.7%) | 63 / 223 (28.3%) |
| Tourism and Hospitality | 108 | 11 / 108 (10.2%) | 35 / 108 (32.4%) | 8 / 108 (7.4%) | 31 / 108 (28.7%) | 21 / 108 (19.4%) |
| Higher Education and Research | 230 | 14 / 230 (6.1%) | 46 / 230 (20.0%) | 5 / 230 (2.2%) | 106 / 230 (46.1%) | 83 / 230 (36.1%) |
| Operations Research | 504 | 43 / 504 (8.5%) | 267 / 504 (53.0%) | 38 / 504 (7.5%) | 151 / 504 (30.0%) | 155 / 504 (30.8%) |
| Statistics | 233 | 20 / 233 (8.6%) | 138 / 233 (59.2%) | 18 / 233 (7.7%) | 122 / 233 (52.4%) | 107 / 233 (45.9%) |
| AI | 1,254 | 131 / 1,254 (10.4%) | 580 / 1,254 (46.3%) | 85 / 1,254 (6.8%) | 186 / 1,254 (14.8%) | 182 / 1,254 (14.5%) |
Finance#
Dataset families: Economic Policy Uncertainty index: 18 / 447 papers; S&P 500: 15 / 447 papers; VIX: 11 / 447 papers; Climate Policy Uncertainty index: 8 / 447 papers; CSMAR: 8 / 447 papers
Methods and equations: Difference-in-differences: 32 / 447 papers; Instrumental variables (two-stage least squares): 28 / 447 papers; Ordinary least squares (OLS): 27 / 447 papers; GARCH: 25 / 447 papers; Vector autoregression (VAR): 20 / 447 papers
Accounting#
Dataset families: 10-K filings: 1 / 37 papers; Australian Credit (UCI): 1 / 37 papers; BoardEx: 1 / 37 papers; S&P 500: 1 / 37 papers; SEC EDGAR: 1 / 37 papers
Methods and equations: Instrumental variables (two-stage least squares): 3 / 37 papers; Fuzzy-set QCA (fsQCA): 2 / 37 papers; Structural equation modeling (SEM): 2 / 37 papers; Dechow-Dichev accruals quality: 1 / 37 papers; Difference-in-differences: 1 / 37 papers
Economics#
Dataset families: Eurostat: 22 / 898 papers; World Development Indicators (World Bank): 17 / 898 papers; International Energy Agency (IEA): 16 / 898 papers; Economic Policy Uncertainty index: 8 / 898 papers; Labour Force Surveys: 8 / 898 papers
Methods and equations: Difference-in-differences: 65 / 898 papers; Ordinary least squares (OLS): 49 / 898 papers; Instrumental variables (two-stage least squares): 47 / 898 papers; Logistic regression (logit): 46 / 898 papers; Two-way fixed-effects panel regression: 27 / 898 papers
Health Economics and Policy#
Dataset families: Global Burden of Disease: 7 / 320 papers; CHARLS: 4 / 320 papers; Demographic and Health Surveys (DHS): 4 / 320 papers; Understanding Society / BHPS: 4 / 320 papers; WITS / TRAINS tariff data: 4 / 320 papers
Methods and equations: Quality-adjusted life year (QALY): 27 / 320 papers; Incremental cost-effectiveness ratio (ICER): 26 / 320 papers; Logistic regression (logit): 17 / 320 papers; Two-way fixed-effects panel regression: 12 / 320 papers; Ordinary least squares (OLS): 7 / 320 papers
Management#
Dataset families: World Development Indicators (World Bank): 9 / 371 papers; Eurostat: 6 / 371 papers; LinkedIn: 6 / 371 papers; Twitter / X: 6 / 371 papers; Amazon Mechanical Turk: 3 / 371 papers
Methods and equations: Structural equation modeling (SEM): 36 / 371 papers; Mediation model (indirect effect): 34 / 371 papers; Cronbach's alpha: 19 / 371 papers; Variance inflation factor: 17 / 371 papers; Fuzzy-set QCA (fsQCA): 15 / 371 papers
Marketing#
Dataset families: Facebook: 4 / 121 papers; Amazon Mechanical Turk: 2 / 121 papers; Prolific: 2 / 121 papers; Twitter / X: 2 / 121 papers; Amazon reviews: 1 / 121 papers
Methods and equations: Structural equation modeling (SEM): 23 / 121 papers; Mediation model (indirect effect): 10 / 121 papers; Composite reliability: 8 / 121 papers; Average variance extracted (AVE): 5 / 121 papers; Cronbach's alpha: 5 / 121 papers
Information Systems#
Dataset families: Facebook: 7 / 223 papers; Twitter / X: 4 / 223 papers; Amazon Mechanical Turk: 3 / 223 papers; Weibo: 3 / 223 papers; YouTube / TikTok: 3 / 223 papers
Methods and equations: Structural equation modeling (SEM): 12 / 223 papers; F1 score: 9 / 223 papers; Logistic regression (logit): 6 / 223 papers; Maximum likelihood estimation: 6 / 223 papers; ROC curve and AUC: 6 / 223 papers
Tourism and Hospitality#
Dataset families: TripAdvisor: 3 / 108 papers; Twitter / X: 2 / 108 papers; YouTube / TikTok: 2 / 108 papers; Airbnb: 1 / 108 papers; Amazon Mechanical Turk: 1 / 108 papers
Methods and equations: Structural equation modeling (SEM): 14 / 108 papers; Mediation model (indirect effect): 11 / 108 papers; Bootstrap: 3 / 108 papers; Cronbach's alpha: 3 / 108 papers; Technology acceptance model (TAM): 3 / 108 papers
Higher Education and Research#
Dataset families: PISA: 2 / 230 papers; USPTO / PatentsView: 2 / 230 papers; World Development Indicators (World Bank): 2 / 230 papers; YouTube / TikTok: 2 / 230 papers; Bureau of Labor Statistics: 1 / 230 papers
Methods and equations: Structural equation modeling (SEM): 10 / 230 papers; Technology acceptance model (TAM): 6 / 230 papers; Journal impact factor: 5 / 230 papers; Maximum likelihood estimation: 5 / 230 papers; Cronbach's alpha: 4 / 230 papers
Operations Research#
Dataset families: OpenStreetMap: 6 / 504 papers; Euro Stoxx / DAX: 4 / 504 papers; UCI Machine Learning Repository: 4 / 504 papers; Eurostat: 3 / 504 papers; S&P 500: 3 / 504 papers
Methods and equations: Linear and integer programming: 87 / 504 papers; Robust optimization: 30 / 504 papers; Vehicle routing problem: 29 / 504 papers; Genetic algorithm: 28 / 504 papers; Logistic regression (logit): 25 / 504 papers
Statistics#
Dataset families: S&P 500: 4 / 233 papers; American Community Survey: 3 / 233 papers; UK Biobank: 2 / 233 papers; ADNI: 1 / 233 papers; CLHLS: 1 / 233 papers
Methods and equations: Maximum likelihood estimation: 34 / 233 papers; Markov chain Monte Carlo (Metropolis-Hastings): 17 / 233 papers; Gaussian process regression: 15 / 233 papers; LASSO: 14 / 233 papers; Logistic regression (logit): 14 / 233 papers
AI#
Dataset families: ImageNet: 29 / 1254 papers; CIFAR-10 / CIFAR-100: 15 / 1254 papers; MNIST / Fashion-MNIST: 11 / 1254 papers; MS COCO: 11 / 1254 papers; Hugging Face Hub: 9 / 1254 papers
Methods and equations: Scaled dot-product attention (Transformer): 133 / 1254 papers; Graph neural network (graph convolution): 92 / 1254 papers; Contrastive loss (InfoNCE): 64 / 1254 papers; Convolutional neural network (CNN): 62 / 1254 papers; F1 score: 61 / 1254 papers
Method, missing data and reproduction#
Each OpenAlex work ID is counted once in its tracked journal’s category. Within each paper, repeated matches for one normalized name count once; multiple names can occur together, so the top-name rows are not additive. The vocabulary groups aliases into families: for example, a family count may combine several dataset versions. Extraction searches the available title, abstract and retrieved full text; a missing match does not establish non-use. Abstract and full-text flags show availability, not whether a match originated in that source. The comparison is not normalized for journal selection, publication lag or missing text. Coverage flags can overlap. Zero-paper rates are undefined.
- Field comparison CSV
- Paper-level input JSON
- Reproduce with Python (standard library)
- Extraction and site methodology
python research-patterns.py research-patterns-input.json > reproduced.csvCite this page
Scholar4AI. (2026). Datasets and methods across research fields. Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/research-patterns
@misc{scholar4ai-research-patterns,
author = {{Scholar4AI}},
title = {Datasets and methods across research fields},
year = {2026},
howpublished = {\url{https://scholar4ai.com/research-patterns}},
urldate = {2026-11-05},
note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}