Anybeat Social Network

A Anybeat dataset of 12,645 users, 49,132 connections, collected by Fire et al. (2012) via Anybeat platform. Each record contains undirected edges between Anybeat users representing social connections in the community platform. Anybeat social network capturing user connections in a public gathering place where people interact with others from around their neighborhood or across the world. Suitable for link prediction, social network analysis, community detection, online community behavior studies.

#Anybeat#Link prediction#Niche social network

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Analytics

The interactive network needs JavaScript.

· graph.json

The full graph has 12,645 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

12.6K
Nodes
49.1K
Edges
6.15e-04
Density
1
Components
-0.1234
Assortativity
0.0%
Reciprocity
6.4K
Bridges
Most central nodes
41520.3796
90880.1251
100370.125
16220.07616
99750.07063
97200.07007
108110.06153
10840.05402
17590.04073
48080.03725

Computed over the full corpus.

Record

Catalog key
anybeat
Authors
Fire, M.; Puzis, R.; Elovici, Y.
Year
2012
Source paper
Link Prediction in Highly Fractional Data Sets
DOI / arXiv
10.1007/978-1-4614-5311-6_14
License
See source page for citation/usage terms.
Records
12,645
Nodes
12,645
Edges
49,132
Nodes are
user
Edges are
friendship
Attributes
nodes have no attributes; edges have no attributes
Languages
en
Collected
2012 (2010s)
Tasks
From the graph: link prediction, community detection

Provenance

Originally published at
https://networkrepository.com/soc-anybeat.php link checked
Hosted copy
Mirrored on echo.directory on 2026-10-09, 736.4 KB across 2 files. Checksums in MANIFEST.json.

Citations

Link Prediction in Highly Fractional Data Sets
M. Fire, Rami Puzis, Y. Elovici
2013

44
citations
cited
3
influential citations
7% of all citations

Cited by

Show all 10

Citation data from Semantic Scholar, retrieved 2026-10-19.

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}
}

@article{Fire2012,
  title     = {Link Prediction in Highly Fractional Data Sets},
  author    = {Fire, M. and Puzis, R. and Elovici, Y.},
  journal   = {Handbook of Computational Approaches to Counterterrorism},
  year      = {2012},
  publisher = {Springer}
}

@inproceedings{nr,
  title     = {The Network Data Repository with Interactive Graph Analytics and Visualization},
  author    = {Ryan A. Rossi and Nesreen K. Ahmed},
  booktitle = {AAAI},
  url       = {https://networkrepository.com},
  year      = {2015}
}

APA

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

Fire, M., Puzis, R., & Elovici, Y. (2012). Anybeat Social Network [Data set]. https://doi.org/10.1007/978-1-4614-5311-6_14

MLA

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

Fire, M., et al. Anybeat Social Network. 2012, doi.org/10.1007/978-1-4614-5311-6_14.

BibTeX · RIS · CSL-JSON

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