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Federico Battiston
Queen Mary University of London
25Publications
10H-index
384Citations
Publications 25
Newest
Published on Aug 28, 2019in arXiv: Physics and Society
Milan Janosov , Federico Musciotto + 1 AuthorsGerardo Iñiguez11
Estimated H-index: 11
(CEU: Central European University)
Music has been one of the strongest forms of cultural expression and identity for thousands of years and has evolved into a strongly collaborative artistic domain. While the emergence of success in music has been studied at large, the link between individual success and collaboration has not yet been fully uncovered. Here we aim to fill this gap by analyzing longitudinal data on the co-releasing and mentoring patterns of tens of thousands of electronic music artists, the most popular of them app...
Published on 2019in Science Advances
Andrea Bamberg Migliano17
Estimated H-index: 17
(UCL: University College London),
Federico Battiston10
Estimated H-index: 10
(CEU: Central European University)
+ 7 AuthorsJesús Gómez-Gardeñes36
Estimated H-index: 36
(University of Zaragoza)
Published on Jun 21, 2019in arXiv: Pattern Formation and Solitons
Giulia Cencetti2
Estimated H-index: 2
,
Federico Battiston10
Estimated H-index: 10
+ 1 AuthorsDuccio Fanelli17
Estimated H-index: 17
Almost 70 years ago A. Turing showed how species diffusion can lead to the emergence of coherent patterns in otherwise stable reactive systems. In this letter, we introduce a novel mechanism to generate spontaneous patterns even in absence of diffusion. We consider a class of purely reactive systems, where immobile species associated to distinct patches, the nodes of a network, interact both locally and at a long-range, as specified by couplings encoded in an (interaction) adjacency matrix. Non ...
Published on Mar 28, 2019in New Journal of Physics3.77
Giulia Cencetti2
Estimated H-index: 2
,
Federico Battiston10
Estimated H-index: 10
Diffusion describes the motion of microscopic entities from regions of high concentration to regions of low concentration. In multiplex networks, flows can occur both within and across layers, and super-diffusion, a regime where the time scale of the multiplex to reach equilibrium is smaller than that of single networks in isolation, can emerge due to the interplay of these two mechanisms. In the limits of strong and weak inter-layer couplings multiplex diffusion has been linked to the spectrum ...
Published on Jan 1, 2019in arXiv: Physics and Society
Federico Battiston10
Estimated H-index: 10
(CEU: Central European University),
Federico Battiston (CEU: Central European University)+ 3 AuthorsRoberta Sinatra16
Estimated H-index: 16
Over the past decades, the diversity of areas explored by physicists has exploded, encompassing new topics from biophysics and chemical physics to network science. However, it is unclear how these new subfields emerged from the traditional subject areas and how physicists explore them. To map out the evolution of physics subfields, here, we take an intellectual census of physics by studying physicists’ careers. We use a large-scale publication data set, identify the subfields of 135,877 physicis...
Published on Jul 16, 2019in arXiv: Physics and Society
Luis Natera , Federico Battiston10
Estimated H-index: 10
+ 1 AuthorsMichael Szell (ITU: IT University of Copenhagen)
Urban transportation networks, from sidewalks and bicycle paths to streets and rail lines, provide the backbone for movement and socioeconomic life in cities. These networks can be understood as layers of a larger multiplex transport network. Because most cities are car-centric, the most developed layer is typically the street layer, while other layers can be highly disconnected. To make urban transport sustainable, cities are increasingly investing to develop their bicycle networks. However, gi...
Published on 2018in arXiv: Neurons and Cognition
Jérémy Guillon3
Estimated H-index: 3
,
Mario Chavez26
Estimated H-index: 26
+ 7 AuthorsFabrizio De Vico Fallani6
Estimated H-index: 6
In Alzheimer's disease (AD), the progressive atrophy leads to aberrant network reconfigurations both at structural and functional levels. In such network reorganization, the core and peripheral nodes appear to be crucial for the prediction of clinical outcome due to their ability to influence large-scale functional integration. However, the role of the different types of brain connectivity in such prediction still remains unclear. Using a multiplex network approach we integrated information from...
Published on Nov 5, 2018in Physical Review E2.35
Giulia Cencetti2
Estimated H-index: 2
,
Federico Battiston10
Estimated H-index: 10
+ 1 AuthorsVito Latora57
Estimated H-index: 57
We introduce and study a metapopulation model of random walkers interacting at the nodes of a complex network. The model integrates random relocation moves over the links of the network with local interactions depending on the node occupation probabilities. The model is highly versatile, as the motion of the walkers can be fed on topological properties of the nodes, such as their degree, while any general nonlinear function of the occupation probability of a node can be considered as local react...
Published on Sep 1, 2018in Journal of the Royal Society Interface3.22
Federico Battiston1
Estimated H-index: 1
(QMUL: Queen Mary University of London),
Jérémy Guillon3
Estimated H-index: 3
(University of Paris)
+ 2 AuthorsFabrizio De Vico Fallani23
Estimated H-index: 23
What is the core of the human brain is a fundamental question that has been mainly addressed by studying the anatomical connections between differently specialized areas, thus neglecting the possible contributions from their functional interactions. While many methods are available to identify the core of a network when connections between nodes are all of the same type, a principled approach to define the core when multiple types of connectivity are allowed is still lacking. Here, we introduce ...
Published on 2018in Physical Review E2.35
Vanesa Avalos-Gaytán1
Estimated H-index: 1
,
Juan A. Almendral13
Estimated H-index: 13
+ 4 AuthorsStefano Boccaletti5
Estimated H-index: 5
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