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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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  1. Content type: Research


    Authors: Mary E. Helander and Sarah McAllister

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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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On the blog: Jazz bands succeed by missing links among musicians

Jazz bands succeed by missing links among musicians © Pixabay, CC0 Public domainWhat makes a tune successful? Does musical innovation happen through individual genius or is it the result of teamwork? Balazs Vedres investigates the levels of creative exchange in the the jazz world, and the ways in which these can foster (or limit) musical success. Read the full study 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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