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Structural measures for multiplex networks.
- F. Battiston, V. Nicosia, V. Latora
- Computer SciencePhysical review. E, Statistical, nonlinear, and…
- 14 August 2013
This paper presents a general framework to describe and study multiplex networks, whose links are either unweighted or weighted, and proposes a series of measures to characterize the multiplexicity of the systems in terms of basic node and link properties.
Extending the definition of modularity to directed graphs with overlapping communities
This paper starts from the definition of a modularity function, given by Newman to evaluate the goodness of network community decompositions, and extends it to the more general case of directed graphs with overlapping community structures.
Geo-spotting: mining online location-based services for optimal retail store placement
This paper studies the predictive power of various machine learning features on the popularity of retail stores in the city through the use of a dataset collected from Foursquare in New York, suggesting that the retail success of a business may depend on multiple factors.
Structural reducibility of multilayer networks.
This work introduces a method based on quantum theory to reduce the number of layers to a minimum while maximizing the distinguishability between the multilayer network and the corresponding aggregated graph.
Defecting or Not Defecting: How to “Read” Human Behavior during Cooperative Games by EEG Measurements
Graph analysis of hyper-brain networks constructed from the EEG scanning of 26 couples of individuals playing the Iterated Prisoner's Dilemma reveals the possibility to predict non-cooperative interactions during the decision-making phase.
Graph Metrics for Temporal Networks
- V. Nicosia, J. Tang, C. Mascolo, Mirco Musolesi, G. Russo, V. Latora
- Computer ScienceArXiv
- 3 June 2013
This chapter discusses how to represent temporal networks and the definitions of walks, paths, connectedness and connected components valid for graphs in which the links fluctuate over time, and focuses on temporal node–node distance.
Analysing information flows and key mediators through temporal centrality metrics
It is argued that dynamically evolving network topologies are inherent in many systems, including real online social and technological networks: fortunately the nature of these systems is such that they allow the gathering of large quantities of finegrained temporal data on interactions amongst the network members.
Elementary processes governing the evolution of road networks
The empirical analysis of a unique data set regarding almost 200 years of evolution of the road network in a large area located north of Milan (Italy) finds that urbanisation is characterised by the homogenisation of cell shapes, and by the stability throughout time of high–centrality roads which constitute the backbone of the urban structure.
Measuring and modelling correlations in multiplex networks
This work introduces various measures to characterize correlations in the activity of the nodes and in their degree at the different layers and between activities and degrees and shows that real-world networks exhibit indeed nontrivial multiplex correlations.
Complex Networks: Principles, Methods and Applications
This textbook presents a detailed overview of the new theory and methods of network science, covering algorithms for graph exploration, node ranking and network generation, among the others, and allows students to experiment with network models and real-world data sets.