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Graph Anomaly Detection datasets

archive 2025-07-28

3 datasets carry the task tag "Graph Anomaly Detection" (the task itself: Graph Anomaly Detection), ordered by the archive's paper count. Page 1 of 1: 3 shown of 3. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

Graph Anomaly Detection datasets 1–3 of 3

The Yelp Dataset is a valuable resource for academic research, teaching, and learning.
86 papers · 15 benchmarks
Yelp-Fraud (Multi-relational Graph Dataset for Yelp Spam Review Detection)
Yelp-Fraud is a multi-relational graph dataset built upon the Yelp spam review dataset, which can be used in evaluating graph-based node classification, fraud detection, and anomaly detection models.
13 papers · 3 benchmarks
Amazon-Fraud (Multi-relational Graph Dataset for Amazon Fraudulent Account Detection)
Amazon-Fraud is a multi-relational graph dataset built upon the Amazon review dataset, which can be used in evaluating graph-based node classification, fraud detection, and anomaly detection models.
8 papers · 3 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.