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Title: Syntgen: a system to generate temporal networks with user-specified topology

Abstract

Abstract In the last few years, the study of temporal networks has progressed markedly. The evolution of clusters of nodes (or communities) is one of the major focus of these studies. However, the time dimension increases complexity, introducing new constructs and requiring novel and enhanced algorithms. In spite of recent improvements, the relative scarcity of timestamped representations of empiric networks, with known ground truth, hinders algorithm validation. A few approaches have been proposed to generate synthetic temporal networks that conform to static topological specifications while in general adopting an ad hoc approach to temporal evolution. We believe there is still a need for a principled synthetic network generator that conforms to problem domain topological specifications from a static as well as temporal perspective. Here, we present such a system. The unique attributes of our system include accepting arbitrary node degree and cluster size distributions and temporal evolution under user control, while supporting tunable joint distribution and temporal correlation of node degrees. Theoretical contributions include the analysis of conditions for graphic sequences of inter- and intracluster node degrees and cluster sizes and the development of a heuristic to search for the cluster membership of nodes that minimizes the shared information distancemore » between clusterings. Our work shows that this system is capable of generating networks under user controlled topology with up to thousands of nodes and hundreds of clusters with strong topology adherence. Much larger networks are possible with relaxed requirements. The generated networks support algorithm validation as well as problem domain analysis.« less

Authors:
 [1];  [2];  [1];
  1. ISTAR, ISCTE-Instituto Universitário de Lisboa, Lisbon, Portugal
  2. IT-IUL Instituto de Telecomunicações, ISCTE-Instituto Universitário de Lisboa, Lisbon, Portugal
Publication Date:
Sponsoring Org.:
USDOE Office of Nuclear Energy (NE), Nuclear Fuel Cycle and Supply Chain
OSTI Identifier:
1571687
Grant/Contract Number:  
UID/Multi/04466/2019; UID/EEA/50008/2019
Resource Type:
Published Article
Journal Name:
Journal of Complex Networks (Online)
Additional Journal Information:
Journal Name: Journal of Complex Networks (Online) Journal Volume: 8 Journal Issue: 4; Journal ID: ISSN 2051-1329
Publisher:
Oxford University Press
Country of Publication:
United Kingdom
Language:
English

Citation Formats

Pereira, Luis Ramada, Lopes, Rui J., Louçã, Jorge, and Mendes, ed., Jose. Syntgen: a system to generate temporal networks with user-specified topology. United Kingdom: N. p., 2019. Web. doi:10.1093/comnet/cnz039.
Pereira, Luis Ramada, Lopes, Rui J., Louçã, Jorge, & Mendes, ed., Jose. Syntgen: a system to generate temporal networks with user-specified topology. United Kingdom. doi:10.1093/comnet/cnz039.
Pereira, Luis Ramada, Lopes, Rui J., Louçã, Jorge, and Mendes, ed., Jose. Thu . "Syntgen: a system to generate temporal networks with user-specified topology". United Kingdom. doi:10.1093/comnet/cnz039.
@article{osti_1571687,
title = {Syntgen: a system to generate temporal networks with user-specified topology},
author = {Pereira, Luis Ramada and Lopes, Rui J. and Louçã, Jorge and Mendes, ed., Jose},
abstractNote = {Abstract In the last few years, the study of temporal networks has progressed markedly. The evolution of clusters of nodes (or communities) is one of the major focus of these studies. However, the time dimension increases complexity, introducing new constructs and requiring novel and enhanced algorithms. In spite of recent improvements, the relative scarcity of timestamped representations of empiric networks, with known ground truth, hinders algorithm validation. A few approaches have been proposed to generate synthetic temporal networks that conform to static topological specifications while in general adopting an ad hoc approach to temporal evolution. We believe there is still a need for a principled synthetic network generator that conforms to problem domain topological specifications from a static as well as temporal perspective. Here, we present such a system. The unique attributes of our system include accepting arbitrary node degree and cluster size distributions and temporal evolution under user control, while supporting tunable joint distribution and temporal correlation of node degrees. Theoretical contributions include the analysis of conditions for graphic sequences of inter- and intracluster node degrees and cluster sizes and the development of a heuristic to search for the cluster membership of nodes that minimizes the shared information distance between clusterings. Our work shows that this system is capable of generating networks under user controlled topology with up to thousands of nodes and hundreds of clusters with strong topology adherence. Much larger networks are possible with relaxed requirements. The generated networks support algorithm validation as well as problem domain analysis.},
doi = {10.1093/comnet/cnz039},
journal = {Journal of Complex Networks (Online)},
number = 4,
volume = 8,
place = {United Kingdom},
year = {2019},
month = {10}
}

Journal Article:
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DOI: 10.1093/comnet/cnz039

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Works referenced in this record:

Comparing clusterings—an information based distance
journal, May 2007


Benchmark Generator for Dynamic Overlapping Communities in Networks
conference, November 2017

  • Sengupta, Neha; Hamann, Michael; Wagner, Dorothea
  • 2017 IEEE International Conference on Data Mining (ICDM)
  • DOI: 10.1109/ICDM.2017.51

$\text{RD}\small{\text{YN}}$ : graph benchmark handling community dynamics
journal, July 2017


Power-Law Distributions in Empirical Data
journal, November 2009

  • Clauset, Aaron; Shalizi, Cosma Rohilla; Newman, M. E. J.
  • SIAM Review, Vol. 51, Issue 4
  • DOI: 10.1137/070710111

Community detection algorithms: A comparative analysis
journal, November 2009


No Graph is Perfect
journal, October 1967

  • Behzad, Mehdi; Chartrand, Gary
  • The American Mathematical Monthly, Vol. 74, Issue 8
  • DOI: 10.2307/2315277

Tracking the Evolution of Communities in Dynamic Social Networks
conference, August 2010

  • Greene, Derek; Doyle, Dónal; Cunningham, Pádraig
  • 2010 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2010)
  • DOI: 10.1109/ASONAM.2010.17

Fast unfolding of communities in large networks
journal, October 2008

  • Blondel, Vincent D.; Guillaume, Jean-Loup; Lambiotte, Renaud
  • Journal of Statistical Mechanics: Theory and Experiment, Vol. 2008, Issue 10
  • DOI: 10.1088/1742-5468/2008/10/P10008

Evolution of networks
journal, June 2002


Quantifying social group evolution
journal, April 2007

  • Palla, Gergely; Barabási, Albert-László; Vicsek, Tamás
  • Nature, Vol. 446, Issue 7136
  • DOI: 10.1038/nature05670

Random graphs with arbitrary degree distributions and their applications
journal, July 2001


Community detection in networks: A user guide
journal, November 2016


Cut-offs and finite size effects in scale-free networks
journal, March 2004

  • Bogu��, M.; Pastor-Satorras, R.; Vespignani, A.
  • The European Physical Journal B - Condensed Matter, Vol. 38, Issue 2
  • DOI: 10.1140/epjb/e2004-00038-8

Resolution limit in community detection
journal, December 2006

  • Fortunato, S.; Barthelemy, M.
  • Proceedings of the National Academy of Sciences, Vol. 104, Issue 1
  • DOI: 10.1073/pnas.0605965104

Benchmark model to assess community structure in evolving networks
journal, July 2015


The many aspects of counting lattice points in polytopes
journal, August 2005


The Distribution of the Flora in the Alpine Zone.1
journal, February 1912


A simple proof of the Erdos-Gallai theorem on graph sequences
journal, February 1986


A Comparative Analysis of Community Detection Algorithms on Artificial Networks
journal, August 2016

  • Yang, Zhao; Algesheimer, René; Tessone, Claudio J.
  • Scientific Reports, Vol. 6, Issue 1
  • DOI: 10.1038/srep30750

A short constructive proof of the Erdős–Gallai characterization of graphic lists
journal, February 2010

  • Tripathi, Amitabha; Venugopalan, Sushmita; West, Douglas B.
  • Discrete Mathematics, Vol. 310, Issue 4
  • DOI: 10.1016/j.disc.2009.09.023

Benchmark graphs for testing community detection algorithms
journal, October 2008


Mixing patterns in networks
journal, February 2003


A complete anytime algorithm for number partitioning
journal, December 1998