Cryptocurrencies return cross-predictability and technological similarity yield information on risk propagation market segmentation. To investigate these effects, we build a time-varying network for cryptocurrencies, based the evolution of similarities. We develop dynamic covariate-assisted spectral clustering method to consistently estimate latent community structure cryptocurrencies that acco...

Maxime Lucas, 2, ∗ Duccio Fanelli, † Timoteo Carletti, ‡ and Julien Petit 4, § Department of Physics, Lancaster University, Lancaster LA1 4YB, United Kingdom Dipartimento di Fisica e Astronomia, Università di Firenze, INFN and CSDC, Via Sansone 1, 50019 Sesto Fiorentino, Firenze, Italy naXys, Namur Institute for Complex Systems, University of Namur, B5000 Namur, Belgium Department of Mathematic...

A stream of unstructured news can be a valuable source of hidden relations between different entities, such as financial institutions, countries, or persons. We present an approach to continuously collect online news, recognize relevant entities in them, and extract time-varying networks. The nodes of the network are the entities, and the links are their co-occurrences. We present a method to e...

We propose generalizations of a number of standard network models, including the classic random graph, the configuration model, and the stochastic block model, to the case of time-varying networks. We assume that the presence and absence of edges are governed by continuous-time Markov processes with rate parameters that can depend on properties of the nodes. In addition to computing equilibrium...

HTTP-based video streaming technologies allow for flexible rate selection strategies that account for time-varying network conditions. Such rate changes may adversely affect the user’s Quality of Experience; hence online prediction of the timevarying subjective quality can lead to perceptually optimized bitrate allocation policies. Recent studies have proposed to use dynamic network approaches ...

The formation of network structure is mainly influenced by an individual node’s activity and its memory, where activity can usually be interpreted as the individual inherent property and memory can be represented by the interaction strength between nodes. In our study, we define the activity through the appearance pattern in the time-aggregated network representation, and quantify the memory th...

The Temporal Network Visualizer is an experimental system to perform real-time visualization of time varying network oriented data. It builds upon the concept of stripcharts to augment a user's memory of past events, enhancing the user's ability to recognize patterns that occur across time as well as space, patterns that we associate with causality. Examples are given for visualizing transactio...

We study the problem of computing minimum-cost paths through a time-varying network, in which the travel time and travel cost of each arc are known functions of one’s departure time along the arc. For some problem instances, the ability to wait at nodes may allow for less costly paths through the network. When waiting is allowed, it is constrained by a (potentially time-varying) waiting policy ...

1. Theory of graph-theoretical data analysis: a series of possible projects on the conceptual and mathematical extensions of techniques for the representation of data as graphs, and the coarsegraining of such representations. These include topics such as: * time-varying networks and their partitions: detecting break points using multidimensional algorithms * development of notions of robustness...