Moltbook — AI Agent Social Network
Moltbook, a social network whose members are autonomous AI agents (Hugging Face jscmp4/Moltbook, 2025): 100,590 agent profiles, 3,352,520 posts and 16,663,266 comments. The graph links agents to the posts and comments they wrote and comments to their posts (20,199,253 nodes, 36,678,988 edges). Suitable for research on AI agent behaviour and social dynamics.
Cite this dataset at
moltbook.echo.directory
Analytics
The full graph has 20,199,253 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.
Topic 0
Topic 1
Topic 2
Topic 3
Topic 4
Topic 5
Topic 6
Topic 7
Topic 8
Topic 9
Topic 10
Topic 11
Show all 329 topics
Topic 12
Topic 13
Topic 14
Topic 15
Topic 16
Topic 17
Topic 18
Topic 19
Topic 20
Topic 21
Topic 22
Topic 23
Topic 24
Topic 25
Topic 26
Topic 27
Topic 28
Topic 29
Topic 30
Topic 31
Topic 32
Topic 33
Topic 34
Topic 35
Topic 36
Topic 37
Topic 38
Topic 39
Topic 40
Topic 41
Topic 42
Topic 43
Topic 44
Topic 45
Topic 46
Topic 47
Topic 48
Topic 49
Topic 50
Topic 51
Topic 52
Topic 53
Topic 54
Topic 55
Topic 56
Topic 57
Topic 58
Topic 59
Topic 60
Topic 61
Topic 62
Topic 63
Topic 64
Topic 65
Topic 66
Topic 67
Topic 68
Topic 69
Topic 70
Topic 71
Topic 72
Topic 73
Topic 74
Topic 75
Topic 76
Topic 77
Topic 78
Topic 79
Topic 80
Topic 81
Topic 82
Topic 83
Topic 84
Topic 85
Topic 86
Topic 87
Topic 88
Topic 89
Topic 90
Topic 91
Topic 92
Topic 93
Topic 94
Topic 95
Topic 96
Topic 97
Topic 98
Topic 99
Topic 100
Topic 101
Topic 102
Topic 103
Topic 104
Topic 105
Topic 106
Topic 107
Topic 108
Topic 109
Topic 110
Topic 111
Topic 112
Topic 113
Topic 114
Topic 115
Topic 116
Topic 117
Topic 118
Topic 119
Topic 120
Topic 121
Topic 122
Topic 123
Topic 124
Topic 125
Topic 126
Topic 127
Topic 128
Topic 129
Topic 130
Topic 131
Topic 132
Topic 133
Topic 134
Topic 135
Topic 136
Topic 137
Topic 138
Topic 139
Topic 140
Topic 141
Topic 142
Topic 143
Topic 144
Topic 145
Topic 146
Topic 147
Topic 148
Topic 149
Topic 150
Topic 151
Topic 152
Topic 153
Topic 154
Topic 155
Topic 156
Topic 157
Topic 158
Topic 159
Topic 160
Topic 161
Topic 162
Topic 163
Topic 164
Topic 165
Topic 166
Topic 167
Topic 168
Topic 169
Topic 170
Topic 171
Topic 172
Topic 173
Topic 174
Topic 175
Topic 176
Topic 177
Topic 178
Topic 179
Topic 180
Topic 181
Topic 182
Topic 183
Topic 184
Topic 185
Topic 186
Topic 187
Topic 188
Topic 189
Topic 190
Topic 191
Topic 192
Topic 193
Topic 194
Topic 195
Topic 196
Topic 197
Topic 198
Topic 199
Topic 200
Topic 201
Topic 202
Topic 203
Topic 204
Topic 205
Topic 206
Topic 207
Topic 208
Topic 209
Topic 210
Topic 211
Topic 212
Topic 213
Topic 214
Topic 215
Topic 216
Topic 217
Topic 218
Topic 219
Topic 220
Topic 221
Topic 222
Topic 223
Topic 224
Topic 225
Topic 226
Topic 227
Topic 228
Topic 229
Topic 230
Topic 231
Topic 232
Topic 233
Topic 234
Topic 235
Topic 236
Topic 237
Topic 238
Topic 239
Topic 240
Topic 241
Topic 242
Topic 243
Topic 244
Topic 245
Topic 246
Topic 247
Topic 248
Topic 249
Topic 250
Topic 251
Topic 252
Topic 253
Topic 254
Topic 255
Topic 256
Topic 257
Topic 258
Topic 259
Topic 260
Topic 261
Topic 262
Topic 263
Topic 264
Topic 265
Topic 266
Topic 267
Topic 268
Topic 269
Topic 270
Topic 271
Topic 272
Topic 273
Topic 274
Topic 275
Topic 276
Topic 277
Topic 278
Topic 279
Topic 280
Topic 281
Topic 282
Topic 283
Topic 284
Topic 285
Topic 286
Topic 287
Topic 288
Topic 289
Topic 290
Topic 291
Topic 292
Topic 293
Topic 294
Topic 295
Topic 296
Topic 297
Topic 298
Topic 299
Topic 300
Topic 301
Topic 302
Topic 303
Topic 304
Topic 305
Topic 306
Topic 307
Topic 308
Topic 309
Topic 310
Topic 311
Topic 312
Topic 313
Topic 314
Topic 315
Topic 316
Topic 317
Topic 318
Topic 319
Topic 320
Topic 321
Topic 322
Topic 323
Topic 324
Topic 325
Topic 326
Topic 327
Topic 328
Sampled: text metrics from 50K of 23.4M records; topic model from 20K. Degree assortativity: exact — Pearson correlation of total degree over every edge (DuckDB) Bridge bottleneck count: exact — biconnected components of the undirected graph (NetworKit) Connected components: exact — connected components (NetworKit) Density: exact Reciprocity rate: exact (DuckDB) Top 10 centrality hubs: exact — full degree count (DuckDB)
Record
- Catalog key
moltbook- Authors
- Dube, Taksch
- Year
- 2026
- Source paper
- Moltbook Social Interactions Dataset
- DOI / arXiv
- 10.5281/zenodo.19470480
- License
- CC BY 4.0 (CC-BY-4.0)
- Records
- 3,352,520
- Nodes
- 20,199,253
- Edges
- 36,678,988
- Nodes are
- agent / post / comment
- Edges are
- created / commented
- Attributes
- nodes have attributes; edges have attributes
- Text corpus
- post text
- Languages
- en
- Collected
- 2025 (2020s)
- Tasks
- From the graph: link prediction, community detection
- Region
- Global (inferred: the platform is used worldwide)
Provenance
- Originally published at
- https://huggingface.co/datasets/jscmp4/Moltbook link checked
- Hosted copy
- Mirrored on echo.directory on 2026-10-02, 24.0 GB across 3 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}
}
@misc{https://doi.org/10.5281/zenodo.19470480,
doi = {10.5281/ZENODO.19470480},
url = {https://zenodo.org/doi/10.5281/zenodo.19470480},
author = {Dube, Taksch},
keywords = {social media, social network analysis, moltbook, AI agents, conversation analysis, longitudinal dataset},
title = {Moltbook Social Interactions Dataset},
publisher = {Zenodo},
year = {2026},
copyright = {Creative Commons Attribution 4.0 International}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Dube, T. (2026). Moltbook — AI Agent Social Network [Data set]. https://doi.org/10.5281/zenodo.19470480
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Dube, Taksch. Moltbook — AI Agent Social Network. 2026, doi.org/10.5281/zenodo.19470480.
