The Dataset Viewer has been disabled on this dataset.
NEExT Egonet Experiment Datasets
Single-graph network datasets with per-node class labels, curated for egonet-based node classification with NEExT: each node's k-hop egonet becomes a subgraph, subgraphs are embedded, and nodes are classified by their egonet embeddings.
Every dataset folder contains:
card.md— information card: task, stats, source, license, citation, caveatsmetadata.json— machine-readable: source URLs, sha256 checksums, per-graph stats, conversion detailsneext/— NEExT-ready tables per graph:edges.csv/nodes.csvand Parquet mirrors (edges.parquet/nodes.parquet; for coauthor-cs, coauthor-physics and reddit-graphsage the Parquet nodes include full feature matrices omitted from CSV for size)source/— original upstream files, unmodified, hash-recorded
Table contract: edges (src_node_id,dest_node_id) + nodes (node_id, <label>, features...),
int64 node IDs, undirected deduplicated edges, fully-populated label column.
Licensing: each dataset keeps its upstream license/terms — see the per-dataset card.md.
This repository is a research mirror; cite the original authors listed in each card.
Datasets
| dataset | task | band | graphs | nodes | edges | classes | label | license |
|---|---|---|---|---|---|---|---|---|
| actor | Actor category classification | medium | 1 | 7,600 | 26,659 | 5 | actor_class |
Not stated (geom-gcn repo) |
| airports | Airport activity-level classification | small | 3 | 1,720 | 20,595 | 4 | activity_quartile |
MIT (struc2vec repository) |
| amazon-computers | Product category classification (co-purchase) | medium | 1 | 13,752 | 245,861 | 10 | category |
MIT (shchur/gnn-benchmark packaging) |
| amazon-photo | Product category classification (co-purchase) | medium | 1 | 7,650 | 119,081 | 8 | category |
MIT (shchur packaging) |
| amazon-ratings | Product rating-class prediction | medium | 1 | 24,492 | 93,050 | 5 | rating_class |
MIT (yandex-research) |
| bitcoin-otc | Fraudulent-user detection (derived labels) | small | 1 | 5,881 | 21,492 | 3 | trust_label |
SNAP research use; cite |
| blogcatalog | Blogger interest-group classification | medium | 1 | 7,460 | 131,034 | 38 | group |
deepwalk repo GPL-3.0; data from ASU social computing repository |
| books | Outlier book detection (Amazon co-purchase) | small | 1 | 1,418 | 3,695 | 2 | is_outlier |
MIT (pygod-team/data) |
| citeseer | Paper topic classification (citation network) | small | 1 | 3,312 | 4,536 | 6 | subject |
LINQS research distribution |
| coauthor-cs | Research-field classification (co-authorship) | medium | 1 | 18,333 | 81,894 | 15 | field |
MIT (shchur packaging) |
| coauthor-physics | Research-field classification (co-authorship) | medium | 1 | 34,493 | 247,962 | 5 | field |
MIT (shchur packaging) |
| cora | Paper topic classification (citation network) | small | 1 | 2,708 | 5,278 | 7 | subject |
LINQS research distribution |
| deezer-europe | User gender classification | medium | 1 | 28,281 | 92,752 | 2 | gender |
SNAP; cite FEATHER |
| disney | Outlier movie detection (co-purchase) | small | 1 | 124 | 335 | 2 | is_outlier |
MIT (pygod-team/data) |
| email-eu-core | Department classification from email traffic | small | 1 | 1,005 | 16,064 | 42 | department |
SNAP research use; cite the source papers |
| enron | Email spam detection | medium | 1 | 13,533 | 176,987 | 2 | is_outlier |
MIT (pygod-team/data) |
| facebook-page-page | Page category classification | medium | 1 | 22,470 | 170,823 | 4 | page_type |
MUSAE repo GPL-3.0; cite MUSAE |
| github-developers | Web vs ML developer classification | medium | 1 | 37,700 | 289,003 | 2 | ml_developer |
SNAP / MUSAE; cite MUSAE |
| lastfm-asia | User country classification | medium | 1 | 7,624 | 27,806 | 18 | country |
SNAP; cite FEATHER |
| minesweeper | Mine prediction on a synthetic grid | medium | 1 | 10,000 | 39,402 | 2 | is_mine |
MIT (yandex-research) |
| ogbn-arxiv | arXiv subject-area classification | large | 1 | 169,343 | 1,157,799 | 40 | arxiv_category |
ODC-BY |
| polblogs | Political-leaning classification | small | 1 | 1,490 | 16,715 | 2 | leaning |
Research use; cite Adamic & Glance |
| pubmed | Paper topic classification (citation network) | medium | 1 | 19,717 | 44,324 | 3 | diabetes_type |
LINQS research distribution |
| questions | User churn prediction | medium | 1 | 48,921 | 153,540 | 2 | is_active |
MIT (yandex-research) |
| reddit-graphsage | Subreddit classification of posts | large | 1 | 232,965 | 11,606,919 | 41 | subreddit |
SNAP research use; cite GraphSAGE |
| reddit-pygod | Banned-user detection | medium | 1 | 10,984 | 78,516 | 2 | is_outlier |
MIT (pygod-team/data) |
| roman-empire | Syntactic-role classification | medium | 1 | 22,662 | 32,927 | 18 | syntactic_role |
MIT (yandex-research) |
| tolokers | Banned crowdworker prediction | medium | 1 | 11,758 | 519,000 | 2 | is_banned |
MIT (yandex-research) |
| twitch | Explicit-content streamer classification | small-medium | 6 | 34,118 | 429,113 | 2 | mature |
SNAP / MUSAE; GPL-3.0 code, cite MUSAE |
| webkb | University web-page classification | small | 3 | 617 | 1,006 | 5 | page_class |
Not stated (geom-gcn repo) |
| Social spam detection | medium | 1 | 8,405 | 377,271 | 2 | is_outlier |
MIT (pygod-team/data) | |
| wikics | CS article branch classification | medium | 1 | 11,701 | 215,603 | 10 | category |
MIT (dataset code); article text CC BY-SA |
| wikipedia-articles | Traffic-level classification (binned) | small-medium | 3 | 19,109 | 400,497 | 5 | traffic_quintile |
SNAP / MUSAE; cite MUSAE |
- Downloads last month
- 62