NEWS #latest

Upcoming event

2017/07/3  |  events

Join us!

The Macfang workshop focuses on the role of space in complex networks. We bring exciting speakers from around the world to foster a leading collaborative view on the emergent field of Network Geometry. A number of topics will be covered, including but not limited to multiplex network geometry, geometric networks at criticality, emerging geometries of evolving networks, and the importance of space in processes such as disease propagation.

World Trade Atlas 1870-2013

2015/11/06  |  academic

Rethinking distance in international trade. World Trade Atlas 1870-2013 

We introduce the World Trade Atlas 1870-2013, a collection of annual World Trade Maps where distance integrates the different dimensions affecting international trade beyond geography. The Atlas informs us about the long-run evolution of the international trade system and shows that, in terms of trade, the world is not flat, it is hyperbolic. The departure from flatness has been increasing since World War I, meaning that differences in trade distances are growing and becoming more hierarchical.Small economies are moving away from the rest of the world, except for their trade with the big economies, while big economies are increasing their chance of getting world-wide connected. At the same time, Preferential Trade Arrangements are not in perfect agreement to natural communities on trade space and have not necessarily effected an internal reduction of trade barriers. We discuss an interpretation in terms of globalization, hierarchicalization, and localization, three forces acting simultaneously to shape the international trade system. Watch the evolution of world trade with this interactive video tool World Trade Atlas 1870-2013

New paper in Nature Physics

2016/12/01  |  academic

Hidden geometric correlations in real multiplex networks

  • Kaj-Kolja Kleineberg, Marián Boguñá, M. Ángeles Serrano & Fragkiskos Papadopoulos

Nature Physics 12, 1076–1081 (2016)

Real networks often form interacting parts of larger and more complex systems. Examples can be found in different domains, ranging from the Internet to structural and functional brain networks. Here, we show that these multiplex systems are not random combinations of single network layers. Instead, they are organized in specific ways dictated by hidden geometric correlations between the layers. We find that these correlations are significant in different real multiplexes, and form a key framework for answering many important questions. Specifically, we show that these geometric correlations facilitate the definition and detection of multidimensional communities, which are sets of nodes that are simultaneously similar in multiple layers. They also enable accurate trans-layer link prediction, meaning that connections in one layer can be predicted by observing the hidden geometric space of another layer. And they allow efficient targeted navigation in the multilayer system using only local knowledge, outperforming navigation in the single layers only if the geometric correlations are sufficiently strong.

Open call - CLOSED

2017/01/23  |  projects

PhD open call, Network Science

We welcome applications for a three-year PhD position within our program of Complex Networks at UB. The gross annual pay is 16.400€ approx.. 

Eligibility Criteria

Candidates must have:

* a Master’s degree at the time of incorporation,

* a strong physics, mathematics and/or computer science background,

* a keen interest in developing and applying computational techniques to real systems from a Network Science perspective,

* an interest in working with real data,

* proved programming skills,

* fluency in spoken and written English.

To apply and for questions, you must send an email to Prof. M. Ángeles Serrano at indicating in the subject of the message “PhD-NS call “+ name surname of the candidate. The application package should include CV and a motivation letter. Selected candidates should be available for interviews (possibly via Skype) and practical tests.

New paper in Scientific Reports

2015/02/22  |  academic

Regulation of burstiness by network-driven activation

We prove that complex networks of interactions have the capacity to regulate and buffer unpredictable fluctuations in production events. We show that non-bursty network-driven activation dynamics can effectively regulate the level of burstiness in the production of nodes, which can be enhanced or reduced. Burstiness can be induced even when the endogenous inter-event time distribution of nodes’ production is non-bursty. We find that hubs tend to be less susceptible to the networked regulatory effects than low degree nodes. Our results have important implications for the analysis and engineering of bursty activity in a range of systems, from communication networks to transcription and translation of genes into proteins in cells.