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Characterization of complex networks: A survey of measurements
TLDR
This article presents a survey of measurements capable of expressing the most relevant topological features of complex networks and includes general considerations about complex network characterization, a brief review of the principal models, and the presentation of the main existing measurements.
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Analyzing and modeling real-world phenomena with complex networks: a survey of applications
TLDR
A diversity of phenomena are surveyed, which may be classified into no less than 11 areas, providing a clear indication of the impact of the field of complex networks.
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Identifying the starting point of a spreading process in complex networks.
TLDR
This paper analyzes three spreading schemes and proposes and validate an effective methodology for the identification of the source nodes based on the calculation of the centrality of the nodes on the sampled network, expressed here by degree, betweenness, closeness, and eigenvector centrality.
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Clustering algorithms: A comparative approach
TLDR
A systematic comparison of 9 well-known clustering methods available in the R language assuming normally distributed data revealed that the default configuration of the adopted implementations was not always accurate, and a simple approach based on random selection of parameters values proved to be a good alternative to improve the performance.
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Keystone species in seed dispersal networks are mainly determined by dietary specialization
TLDR
It is suggested that dietary specialization is key to understand what makes a frugivore species a keystone in seed dispersal networks, and that taxonomic identity also plays a significant role.
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Sensory-Related Neural Activity Regulates the Structure of Vascular Networks in the Cerebral Cortex
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A Systematic Comparison of Supervised Classifiers
TLDR
The default configuration of parameters in Weka was found to provide near optimal performance for most cases, not including methods such as the support vector machine (SVM), and the k-nearest neighbor method frequently allowed the best accuracy.
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The role of centrality for the identification of influential spreaders in complex networks
TLDR
This paper investigates how nine centrality measures correlate with the disease and rumor spreading capabilities of the nodes in different synthetic and real-world networks and proposes a generalization of the random walk accessibility as a new centrality measure and derive analytical expressions for the latter measure for simple network configurations.
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Rich-club phenomenon across complex network hierarchies
TLDR
The authors investigate the existence of the rich-club phenomenon across the hierarchies of several real-world networks and reveal that the presence or absence of this phenomenon in a network does not imply its presence or presence in the network’s successive hierarchies, and that this behavior is even nonmonotonic in some cases.
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Complex networks: The key to systems biology
TLDR
This article is an up-to-date review of the major developments related to the application of complex networks in biology, with special attention focused on the more recent literature.
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