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Outliers in the ABCD Random Graph Model with Community Structure (ABCD+o)

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Complex Networks and Their Applications XI (COMPLEX NETWORKS 2016 2022)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1078))

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Abstract

The Artificial Benchmark for Community Detection graph (ABCD) is a random graph model with community structure and power-law distribution for both degrees and community sizes. The model generates graphs with similar properties as the well-known LFR one, and its main parameter \(\xi \) can be tuned to mimic its counterpart in the LFR model, the mixing parameter \(\mu \). In this paper, we extend the ABCD model to include potential outliers. We perform some exploratory experiments on both the new ABCD+o model as well as a real-world network to show that outliers posses some desired, distinguishable properties.

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Notes

  1. 1.

    https://github.com/bkamins/ABCDGraphGenerator.jl/.

  2. 2.

    https://github.com/tolcz/ABCDeGraphGenerator.jl/.

  3. 3.

    https://github.com/ftheberge/graph-partition-and-measures.

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Author information

Authors and Affiliations

  1. SGH Warsaw School of Economics, Warsaw, Poland

    Bogumił Kamiński

  2. Toronto Metropolitan University, Toronto, ON, Canada

    Paweł Prałat

  3. The Tutte Institute for Mathematics and Computing, Ottawa, ON, Canada

    François Théberge

Authors
  1. Bogumił Kamiński
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  2. Paweł Prałat
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  3. François Théberge
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Corresponding author

Correspondence to Paweł Prałat .

Editor information

Editors and Affiliations

  1. University of Burgundy, Dijon, France

    Hocine Cherifi

  2. Dipartimento di Fisica e Chimica—Emilio Segrè, Università degli Studi Palermo, Palermo, Italy

    Rosario Nunzio Mantegna

  3. Thomas J. Watson College of Engineering and Applied Science, Binghamton University, Binghamton, NY, USA

    Luis M. Rocha

  4. IUT Lumière—Université Lyon 2, University of Lyon, Bron, France

    Chantal Cherifi

  5. Dipartimento di Fisica e Chimica—Emilio Segrè, Università degli Studi Palermo, Palermo, Italy

    Salvatore Micciche

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Kamiński, B., Prałat, P., Théberge, F. (2023). Outliers in the ABCD Random Graph Model with Community Structure (ABCD+o). In: Cherifi, H., Mantegna, R.N., Rocha, L.M., Cherifi, C., Micciche, S. (eds) Complex Networks and Their Applications XI. COMPLEX NETWORKS 2016 2022. Studies in Computational Intelligence, vol 1078. Springer, Cham. https://doi.org/10.1007/978-3-031-21131-7_13

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  • DOI: https://doi.org/10.1007/978-3-031-21131-7_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21130-0

  • Online ISBN: 978-3-031-21131-7

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