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SUMMARY:Centrality in interconnected multilayer networks: mathematical for
 mulation of node versatility and its application to socio-technical system
 s
DTSTART:20161026T123000
DTEND:20161026T133000
DTSTAMP:20260406T230146Z
UID:33cc38ff177b2a463582a80c12f5aac647e51f25486c36aa4a5c6e2e
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Elisa Omodei Department of Computer Engineering and Mathem
 atics\, Rovira i Virgili University\, Tarragona\, Spain\nThe determination
  of the most central agents in complex networks is important because they 
 are responsible for a faster propagation of information\, epidemics\, fail
 ures and congestion\, among others. A challenging problem is to identify t
 hem in networked systems characterized by different types of interactions\
 , forming interconnected multilayer networks. Think for example about the 
 transportation system of a big city\, composed of different but interconne
 cted layers: the street network\, the railway system\, the underground net
 work\, etc. Here we describe a mathematical framework that allows us to ca
 lculate centrality in such networks and rank nodes accordingly\, finding t
 he ones that play the most central roles in the cohesion of the whole stru
 cture\, bridging together different types of relations. These nodes are th
 e most versatile in the multilayer network. We then present some applicati
 ons to different socio-technical systems. First\, we propose a method base
 d on the analysis of bipartite interconnected multilayer networks of citat
 ions and disciplines\, to assess scholars\, institutions and countries int
 erdisciplinary importance. Using data about physics publications and US pa
 tents\, we show that our method allows to reward\, using a quantitative ap
 proach\, scholars and institutions that have carried out interdisciplinary
  work and have had an impact in different scientific areas. Second\, we in
 vestigate the diffusion of microfinance within rural India villages accoun
 ting for the whole multilayer structure of the underlying social networks.
  We define a new measure of node centrality on multilayer networks\, diffu
 sion versatility\, and show that this is a better predictor of microfinanc
 e participation rate than previously introduced measures defined on aggreg
 ated single-layer social networks. Moreover\, we untangle the role played 
 by each social dimension and find that the most prominent role is played b
 y the nodes that are central on layers concerned with trust\, shedding new
  light on the key triggers of the diffusion of microfinance. Finally\, we 
 show that node versatility can be used in the context of air transportatio
 n networks to predict the ordering at which airports arrive to congestion.
  We will then conclude with some perspectives on the application of the fr
 amework multilayer networks and node versatility in the context of urban s
 ystems.
LOCATION:GC B1 10
STATUS:CONFIRMED
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