Month: March 2017

Redundant Interdependencies Boost the Robustness of Multiplex Networks

In the analysis of the robustness of multiplex networks, it is commonly assumed that a node is functioning only if its interdependent nodes are simultaneously functioning. According to this model, a multiplex network becomes more and more fragile as the number of layers increases. In this respect, the addition of a new layer of interdependent nodes to a preexisting multiplex network will never improve its robustness. Whereas such a model seems appropriate to understand the effect of interdependencies in the simplest scenario of a network composed of only two layers, it may seem unsuitable to characterize the robustness of real systems formed by multiple network layers. In fact, it seems unrealistic that a real system evolved, through the development of multiple layers of interactions, towards a fragile structure. In this paper, we introduce a model of percolation where the condition that makes a node functional is that the node is functioning in at least two of the layers of the network. The model reduces to the commonly adopted percolation model for multiplex networks when the number of layers equals two. For larger numbers of layers, however, the model describes a scenario where the addition of new layers boosts the robustness of the system by creating redundant interdependencies among layers. We prove this fact thanks to the development of a message-passing theory that is able to characterize the model in both synthetic and real-world multiplex graphs.


Redundant Interdependencies Boost the Robustness of Multiplex Networks
Filippo Radicchi and Ginestra Bianconi
Phys. Rev. X 7, 011013


NetSci 2017 conference details


Note: Early-bird discount deadline is May 4

International School and Conference on Network Science

June 19-23, Indianapolis, IN (JW Marriott Indianapolis)  |



Day One (Monday, June 19)
Network Structure: Alex Arenas (Universitat Rovira i Virgili)
Contagion and spreading processes on networks: Alessandro Vespignani (Northeastern U)
Day Two (Tuesday, June 20)
Maximum-entropy methods for financial and economic networks: Diego Garlaschelli (Leiden U & Oxford U)
Network Control: Raissa D’Souza (UC Davis)
Learning, Mining, and Networks: Tina Eliassi-Rad (Northeastern U)



Satellite Symposia are full and half-day meetings devoted to particular topics. See full schedule and programs in development:

  1. Controlling Complex Networks: From Biological to Social and Technological Systems
  2. 2nd Workshop on Statistical Physics of Financial and Economic Networks
  3. 1st Annual Consortium for the Society of Young Network Scientists (SYNS)
  4. Cognitive Network Science
  5. Higher-Order Models in Network Science (HONS 2017)
  6. Dynamics on and of Complex Networks – X
  7. Information, Self-Organizing Dynamics and Synchronization on Networks (ISODS III)
  8. Machine Learning in Network Science
  9. Network Neuroscience
  10. Network Medicine: Quantitative interactome and multilayer networks taking medicine beyond the genome
  11. Networks Of Networks: Systemic Risk and Infrastructural Interdependencies (NetONets2017)
  12. NetSciReg’17 — Network Models in Cellular Regulation
  13. Quantifying Success
  14. Social Influence in Networks
  15. Statistical Inference for Network Models
  16. Urban Systems and Networks Science
  17. NetCrime—Structure and Mobility of Crime
  18. Contagion on Networks: Progress and Issues with Models and Data
  19. Network Science for National Defense
  20. Strengthening Reproducibility in Network Science
  21. NetSciEd 6: Satellite Symposium on Network Science and Education
  22. Knowledge Networks in Science and Technology




Keynote Speakers:

Danielle S. Bassett  (U Penn)

Steve Borgatti (U Kentucky)

Jennifer A. Dunne (Sante Fe Institute)


Invited Speakers:

Meeyoung Cha (KAIST)

Alex Fornito (Monash U)

Lise Getoor (UC Santa Cruz)

César A. Hidalgo (MIT)

Shawndra Hill (Microsoft Research NYC & U Penn)

Maximilian Schich (UT Dallas Arts & Technology)

  1. Ángeles Serrano, (U Barcelona)

Roberta Sinatra (Central European U)

Xiaofan Wang (Shanghai Jiao Tong U)


Presentations: The list of abstracts accepted for oral presentations, lightning talks, and posters is available:



NetSci 2017, the International School and Conference on Network Science, will be held in Indianapolis, Indiana from June 19 to 23, 2017. NetSci 2017 aims to bring together leading researchers and practitioners working in the emerging area of network science. The conference fosters interdisciplinary communication and collaboration in network science research across computer and information sciences, physics, mathematics, statistics, the life sciences, neuroscience, environmental sciences, social sciences, finance and business, arts and design.



PROGRAM COMMITTEE CO-CHAIRS: Yong-Yeol Ahn (Indiana University Bloomington), Ciro Cattuto (ISI Foundation) & Tina Eliassi-Rad (Northeastern University)

SATELLITE CO-CHAIRS: Réka Albert (Pennsylvania State University) & Filippo Radicchi (Indiana University Bloomington)

SCHOOL CO-CHAIRS: Santo Fortunato (Indiana University Bloomington) & M. Ángeles Serrano (Universitat de Barcelona)

SPONSORSHIP CO-CHAIRS: Giovanni Ciampaglia & Alessandro Flammini (Indiana University Bloomington)

GENERAL CO-CHAIRS: Fil Menczer & Olaf Sporns (Indiana University Bloomington)


NetSci 2017 is hosted by the Indiana University Network Science Institute ( It is the annual meeting of the Network Science Society (

Questions? Email and

Follow us on Twitter and Facebook: @NetSci2017


Opportunities and Challenges of Trip Generation Data Collection Techniques Using Cellular Networks

We are witnessing how urban areas are reclaiming road space, before devoted exclusively to cars, for pedestrians. With the increase of pedestrian activity, we need to update our existing transportation forecasting models by focusing more on people walking. The first step of extending the current models is to start with collecting information on pedestrians needed for the trip generation phase. This article discusses opportunities and limitations of tracking pedestrian activity by utilizing information provided by cellular networks. In order to track people, regardless of the underlying wireless media, two qualifications must be met: first, unique and anonymous identification, and second, geospatial visibility through time. While the latter requirement can be achieved with techniques that are similar for different wireless media, how to uniquely identify a pedestrian using a cellular network is domain-specific. We show that tracking of pedestrians using cellular networks can be done not only without their constant active participation, but also without disrupting normal cellular service. However, although this method is technically feasible, one should be very careful when wanting to implement it by keeping in mind a very important thing: how to protect people’s privacy.


Opportunities and Challenges of Trip Generation Data Collection Techniques Using Cellular Networks

Iva Bojic ; Yuji Yoshimura ; Carlo Ratti

IEEE Communications Magazine > Volume: 55 Issue: 3


Emergence of communities and diversity in social networks

Understanding how communities emerge is a fundamental problem in social and economic systems. Here, we experimentally explore the emergence of communities in social networks, using the ultimatum game as a paradigm for capturing individual interactions. We find the emergence of diverse communities in static networks is the result of the local interaction between responders with inherent heterogeneity and rational proposers in which the former act as community leaders. In contrast, communities do not arise in populations with random interactions, suggesting that a static structure stabilizes local communities and social diversity. Our experimental findings deepen our understanding of self-organized communities and of the establishment of social norms associated with game dynamics in social networks.