From Nov 2023 to Oct 2026, 57 archived papers mentioned Credit card fraud data (Kaggle, PaySim, IEEE-CIS) in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Feb 2024 (6).
No paper of the tracked journals mentioned Credit card fraud data (Kaggle, PaySim, IEEE-CIS) in the last 30 days (2026-10-06 to 2026-11-04).
From 2017 to 2026 (so far), Credit card fraud data (Kaggle, PaySim, IEEE-CIS) was mentioned in 67 papers in the tracked journals, most of them in AI (59), information systems (3) and finance (2).
17 of them were published in 2025, against 0 in 2017.
Since 2023, the institutions with the most of these papers were Florida Atlantic University (9), Southern University of Science and Technology (6) and Alexandria University (2).
The journals publishing most of them were Journal Of Big Data (15), IEEE Transactions on Neural Networks and Learning Systems (13) and IEEE Transactions on Fuzzy Systems (10).
The most-cited of them is “Feature selection strategies: a comparative analysis of SHAP-value and importance-based methods” (Journal Of Big Data, 2024), with 633 citations.
Papers use Credit card fraud data (Kaggle, PaySim, IEEE-CIS) most often with Kaggle (20), mlg-ulb/creditcardfraud (13) and UCI Machine Learning Repository (6); it has 6 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.
Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)
Archive counts by publication year: a paper counts when its title, abstract or keywords name the dataset, or when OpenAlex's full-text search finds it there (searched for the last 30 days' papers and, by a pass over the past years, for older ones). Names added to the list later are looked for in older papers as the archive is read again.
Papers use Credit card fraud data (Kaggle, PaySim, IEEE-CIS) most often with Kaggle (20), mlg-ulb/creditcardfraud (13) and UCI Machine Learning Repository (6); it has 6 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST. The whole network →
What papers use Credit card fraud data (Kaggle, PaySim, IEEE-CIS) together with (at least 3 papers; lift 1 = chance)
Scholar4AI. (2026). Credit card fraud data (Kaggle, PaySim, IEEE-CIS). Journal and Conference Research Rankings. Retrieved November 4, 2026, from https://scholar4ai.com/datasets/credit-card-fraud-data-kaggle-paysim-ieee-cis
@misc{scholar4ai-datasets-credit-card-fraud-data-kaggle-paysim-ieee-cis,
author = {{Scholar4AI}},
title = {Credit card fraud data (Kaggle, PaySim, IEEE-CIS)},
year = {2026},
howpublished = {\url{https://scholar4ai.com/datasets/credit-card-fraud-data-kaggle-paysim-ieee-cis}},
urldate = {2026-11-04},
note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).