Terrorist Attacks Network (GCN Benchmark)

A Terrorist Attacks dataset of 645 nodes, 3,172 edges, 6 classes, collected by Yang et al. (ICML 2016). Each record contains node features, citation edges, class labels. Terrorist Attacks network with bag-of-words features. Suitable for node classification, semi-supervised learning, graph neural networks.

#Bag of words#Benchmark#Graph neural network#Node classification

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Analytics

The interactive network needs JavaScript.

· graph.json

Node size is centrality, colour is community. Hover a node for details; click one to isolate its community.

645
Nodes
3.2K
Edges
1.53e-02
Density
139
Components
0.9972
Assortativity
0.0%
Reciprocity
81
Bridges
Most central nodes
2560.07609
1020.07453
1110.07453
1180.07453
120.07453
1350.07453
1480.07453
1500.07453
1590.07453
160.07453
Content metrics

645 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

labelavg 2.57 / 5
0std 1.905
feature countμ 10.761 ± 3.783
min 3max 27
is test10.1% true
true 10.1%false 89.9%
3.0
Flesch–Kincaid grade
US school grade level
-1.9
Automated readability index
Frequent terms
100101102103104node_0node_1node_10node_100node_101node_102node_103node_104node_105node_106node_107node_108node_109node_11node_110node_111node_112node_113node_114node_115node_116node_117node_118node_119node_12node_120node_121node_122node_123node_124node_125node_126node_127node_128node_129node_13node_130node_131node_132node_133node_134node_135node_136node_137node_138
Topic clusters

Topic 0

82
12
39
43
44
58
63
86

Topic 1

29
63
36
32
86
81
28
85

Topic 2

33
40
35
60
34
63
80
28

Topic 3

96
85
80
63
86
79
62
31

Topic 4

63
88
86
29
30
53
28
79

Topic 5

79
86
11
33
31
96
62
97

Topic 6

85
97
81
79
31
29
32
72

Topic 7

29
101
81
85
30
28
87
96

Topic 8

45
69
85
61
81
96
54
16

Topic 9

86
63
96
31
14
67
39
82

Topic 10

55
30
51
99
63
81
48
87

Computed over the full corpus.

Record

Catalog key
gcn_terror_attack
Authors
Zhao, Bin; Sen, Prithviraj; Getoor, Lise
Year
2006
Source paper
Entity and relationship labeling in affiliation networks
License
Academic Use (LicenseRef-Research-Only)
Records
645
Nodes
645
Edges
3,172
Nodes are
terrorist attack
Edges are
co-occurrence
Attributes
nodes have no attributes; edges have no attributes
Languages
en
Collected
2016 (2010s)
Tasks
Node classification (multi-class; label) inferred
From the graph: link prediction, community detection

Provenance

Originally published at
https://github.com/kimiyoung/planetoid link checked
Hosted copy
Mirrored on echo.directory on 2026-10-16, 3.4 MB across 80 files. Checksums in MANIFEST.json.

How to cite

BibTeX

@misc{echo2026,
  title  = {ECHO: Exploratory Compendium of Humanity Online},
  author = {Switzer, Braden and Zafarani, Reza},
  year   = {2026},
  url    = {https://echo.directory},
  note   = {Syracuse University}
}

@inproceedings{zhao2006entity,
  title     = {Entity and relationship labeling in affiliation networks},
  author    = {Zhao, Bin and Sen, Prithviraj and Getoor, Lise},
  booktitle = {ICML Workshop on Statistical Network Analysis},
  year      = {2006}
}

APA

Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory

Zhao, B., Sen, P., & Getoor, L. (2006). Terrorist Attacks Network (GCN Benchmark) [Data set]. https://gcn-terror-attack.echo.directory/

MLA

Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.

Zhao, Bin, et al. Terrorist Attacks Network (GCN Benchmark). 2006, gcn-terror-attack.echo.directory/.

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