International MSc and PhD Programs in Complexity Sciences

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2nd Winter School in Complexity Sciences 

"Formal approaches for the representation and analysis of social network structures" 

Lisbon University Institute,  January 11-15, 2010

The 2nd Winter School in Complexity Sciences will take place at the Lisbon University Institute, on January 11-15, 2010. The programme of this edition is organized around the subject "Formal approaches for the representation and analysis of social network structures".

The Winter School is organised in the context of the International Doctoral and Master Programs in Complexity Sciences proposed by the Lisbon University Institute and the Faculty of Sciences of the University of Lisbon. The Winter School is also supported by the ASSYST Coordination Action and the Complex Systems Society. The Winter School will propose a state-of-the-art of the new theories, methodologies and algorithmic proposals to the study of topological features of complex networks. 

Target audience

The sessions are intended for faculty, graduate students, master and PhD students, researchers and others who would like to gain an understanding of the new formal approaches to the representation and interpretation of network structures. 

Organisation

The Winter School will include both theoretical presentations and practical sessions in computer room, allowing presenting and experimenting the most well known and performative software tools for the representation and analysis of networks. The school will provide 10 theoretical sessions of 1:30 each and 5 practical sessions of 2 hours each - a total of 25 hours during 1 week. Sessions will start at 3pm and will end at 8:30pm. This time schedule will allow participants to use the morning and early afternoon free moments to interact with local researchers at the university. 

Programme

Speakers

• David Rodrigues (Lisbon University Institute, PT) - software for the representation and analysis of networks - see the list of software below (practical sessions)
  
• Gergely Palla (Hungarian Academy of Sciences, HU) - 2 theoretical sessions:
  

1. Statistical properties of tagged networks - With the development of complex network theory, our picture of the structure and function of real network systems is getting refined rapidly. The inclusion of node tags (also called as attributes, annotations, properties, categories, features) in the network analysis leads to a richer structure, opening up the possibility for a more comprehensive analysis of the systems under investigation. The lecture will detail the fundamental statistical features and self-similar properties of tagged networks.
2. Multifractal network generator - Generating graphs with varying prescribed properties has attracted great interest recently. We discuss briefly most important approaches related to this topic including e.g., the $dK$-series, the Kronecker-graphs and the exponential random graph model. The main part of the talk focuses on a new approach based on a mapping between suitably chosen singular measures (also called as multifractals) defined on the unit square and sparse infinite networks. Such a mapping has the great potential of allowing for graph theoretical results for a variety of network topologies. A very unique feature of this construction is that the complexity of the generated network is increasing with the size.

1. Theoretical session: Network Topology and Challenge Modelling for Future Internet Resilience - This presentation will begin by motivating the need for accurate network topology models in understanding the Future Internet.  It will then discuss some of the fundamental graph properties and metrics necessary for an understanding of network resilience and survivability.  Models and techniques will be discussed to generate network topologies based on engineering, geography, cost, and population constraints.  Then techniques will be presented to model network challenges, including failures, natural disasters, and attacks.  Finally, a state-space approach to evaluating network resilience will be presented consisting of operational and service dimensions, with example application to the topology and challenge modelling.
2. Research seminar: The Great Plains Environment for Network Innovation (GpENI): a Programmable Testbed for Future Internet Architecture Research - The Great Plains Environment for Network Innovation (GpENI) is an international programmable network testbed centered on a regional optical network in the Midwest US, providing flexible infrastructure across the entire protocol stack. The goal of GpENI is to build a collaborative research infrastructure enabling the community to conduct experiments in future Internet architecture: applications, end-to-end transport, routing and topology, core optical and wireless edge technologies. GpENI is funded in part by the US National Science Foundation GENI (Global Environments for Network Innovation) program and by the EU FIRE (Future Internet Research and Experimentation) Programme. This presentation describes the architecture, topology, and deployment plans and challenges for GpENI in the US, Europe, and Asia. The opportunities for the use of GpENI in such projects as FIRE ResumeNet and FIND PoMo will be discussed, as well as emerging and future collaborations.

1. Self-organization, emergence and the networks model of inquiry - Is the notion of emergence coherent?  (Kim 1999); Computational approaches to emergence and the basic metaphysical questions (Symons 2008a); Networks in Science (Symons 2008b).
2. Causality and Pattern Discovery - Is there a scientifically meaningful notion of causality? Computational mechanics and the epsilon-machines. What makes a pattern real?

1. Practical sessions: software for the representation and analysis of networks - see the list of software below.
2. Theoretical session: about scale and structure issues in networks.
   

1. Community detection in graphs I - In this first lecture I discuss the basic elements of community detection in graphs. After a brief introduction to communities in real networks, I pass to the definition of basic concepts like community and partition. Finally I discuss traditional methods of community detection, used in computer and social science.
2. Community detection in graphs II - Here I present a small selection of popular methods for community detection used nowadays. I will also discuss the problem of finding overlapping communities and hierarchical structure. I conclude with the discussion of two crucial issues of this area, namely the concept of significance of community structure and how methods should be tested and compared to each other.