By Hocine Cherifi, Sabrina Gaito, Walter Quattrociocchi, Alessandra Sala
This e-book highlights state of the art learn within the box of community technology, delivering scientists, researchers and graduate scholars a special chance to compensate for the most recent advances in idea and a mess of purposes. It provides the peer-reviewed court cases of the 5th foreign Workshop on complicated Networks & their purposes (COMPLEX NETWORKS 2016), which came about in Milan over the last week of November 2016. The conscientiously chosen papers are divided into eleven sections reflecting the variety and richness of analysis components within the box. extra particularly, the next subject matters are coated: community versions; community measures; group constitution; community dynamics; Diffusion, epidemics and spreading approaches; Resilience and keep an eye on; community visualization; Social and political networks; Networks in finance and economics; organic and ecological networks; and community analysis.
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Additional resources for Complex Networks & Their Applications V: Proceedings of the 5th International Workshop on Complex Networks and their Applications (COMPLEX NETWORKS 2016)
Cherifi et al. 1007/978-3-319-50901-3_2 17 18 C. L. Staudt, M. Hamann, I. Safro, A. Gutfraind, H. Meyerhenke sensitive, or unavailable in different scales. In the context of developing network analysis algorithms, realistic synthetic graphs allow us to produce experimental results that are representative for what can be observed for real data. Among the main use cases are obfuscation (replacing restricted real data with similar synthetic data), compression (storing only a generator and its parameters instead of large graphs), as well as extrapolation and sampling (generating data at larger or smaller scales).
4 Fitting and generating: processing speed measured in edges/s (size of replica graph / total running time, measured on 100 Facebook graphs) C. L. Staudt, M. Hamann, I. Safro, A. Gutfraind, H. Meyerhenke #$* 26 #$) #$( #$' #$& ! #$% " and fitting schemes, we generate replicas of 100 Facebook networks and test a variety of graph algorithms (see Sec. 2) on both the original and replica sets.
In: WWW, pp. 981–990. ACM (2010) Generating Scaled Replicas of Real-World Complex Networks Christian L. Staudt, Michael Hamann, Ilya Safro, Alexander Gutfraind and Henning Meyerhenke Abstract Research on generative models plays a central role in the emerging field of network science, studying how statistical patterns found in real networks can be generated by formal rules. During the last two decades, a variety of models has been proposed with an ultimate goal of achieving comprehensive realism for the generated networks.