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Featured article: Generating realistic scaled complex networks

ReCoN (d) is the model that best reproduces a set of essential properties of the original network (a) © Staudt et al. 2017During the last two decades, a variety of models has been proposed with an ultimate goal of achieving comprehensive realism for the generated networks. In this study, Christian L. Staudt and team introduce a new generator (ReCoN) and compare its performance to those of the other state-of-the-art network generation methods.

ReCoN proves to be a scalable and effective tool for modeling a given network while preserving important properties at both micro- and macroscopic scales, and for scaling the exemplar data by orders of magnitude in size.

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Modeling, Computation and Prediction in Complex Networks
Guest Editor: Adam Wierzbicki

Special Issue of the 4th International Workshop on Complex Networks and Their Applications
Guest Editors: Chantal Cherifi and Hocine Cherifi

Special Issue on the 7th International Workshop on Complex Networks
Guest Editors: Bruno Gonçalves and Roberta Sinatra

Special Issue on the 5th International Workshop on Complex Networks and Their Applications
Guest Editors: Sabrina Gaito, Walter Quattrociocchi and Alessandra Sala

Special Issue on the 6th International Workshop on Complex Networks and Their Applications
Guest Editors: Sabrina Gaito, Marton Karsai and Hamamache Kheddouci

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Call for papers: Community Structure in Networks

CFP ComNet © T. Nguyen, B. K. Szymanski, Rensselaer Polytechnic InstituteA new article collection dedicated to the cutting edge research advances on community structures in networks, in order to provide a landscape of research progresses and application potentials in related areas, is now open for submissions. 

Guest editors
Gergely Palla, Eötvös University
Hocine Cherifi, Université de Bourgogne
Boleslaw K. Szymanski, Rensselaer Polytechnic Institute

Expression of interest: October 01, 2018
Full paper submission: November 08, 2018

Read more here.

Call for papers: Modeling, Analyzing and Mining Feature-Rich Networks

CFP Fernet © Pixabay, CC0 Creative Commons
We welcome submissions to a new article collection aiming to provide an insight into innovative methods to model, analyze and mine feature-rich networks inspired from different fields, incentivizing domain-driven approaches that can drive the design of novel network models.

Guest editors
Martin Atzmueller, Tilburg University
Sabrina Gaito, University of Milano
Roberto Interdonato, CIRAD
Rushed Kanawati, Paris 13 University
Christine Largeron, University of Lyon
Alessandra Sala, Nokia Bell Labs

Expression of interest: September 21, 2018
Full paper submission: October 28, 2018

More information here.

Aims and scope

Applied Network Science (ANS) is an open-access and strictly peer-reviewed journal giving researchers and practitioners in the field the ability to reach a larger audience. ANS encompasses all established and emerging fields that have been or can be shown to benefit from quantitative network-based modeling. Contributions from all fields of science, technology, medicine and humanities will be considered, in particular from newly emerging research areas formed and developing at the interfaces of presently established sub-disciplines.

The focus of the journal is based on novel or anticipated applications of network sciences, on related techniques that may be used in applications of complex network methodologies, and on innovative modeling approaches that will enhance specific applications and lead to more widespread use of network science concepts. Overall, articles that have a direct application to real world problems form the core publications of this journal.

Ongoing collections

Network Medicine in the era of Big Data in Science and Healthcare​​​​​​​
Guest Editors: Amitabh Sharma, Marc Santolini and Emre Guney

Special Issue of the 6th International Workshop on Complex Networks and Their Applications
Guest Editors: Sabrina Gaito, Marton Karsai and Hamamache Kheddouci

Other article collections can be found here.


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