Watch the presentations of the KNAW Symposium on Networks online!

What do transport, communication and energy networks have in common? How effective are they? How vulnerable are they? How can they be searched and optimized? How does information or an epidemic spread over a network? This symposium seeked answers to these questions through a series of lectures, intended for a broad audience. The titles and abstracts, and the links to the recordings are given below:

 

• Monique Laurent, Centrum Wiskunde & Informatica and Tilburg University – Ordering data with network methods

Understanding which network problems can be solved efficiently is an ongoing quest. We illustrate this algorithmically complex landscape by considering some basic network problems. We also explain how simple network search methods can be used in data analysis to order given objects by their similarities. This is relevant, for instance, for genome sequencing and for relative chronological ranking of archaeological sites.

 

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• Nelly Litvak, University of Twente and Eindhoven University of Technology – Google PageRank and network centrality

The PageRank algorithm was one of Google’s crucial innovations, designed to solve a profound problem: in which order should we arrange web search results for the user? The idea behind PageRank is that a page is important when many important pages link to it. PageRank has been used in many applications beyond web search, from combatting web spam to finding the most endangered biological species. This is because PageRank in fact solves the broader problem of network centrality, a measure used in social networks to find the most central and influential people. We will discuss PageRank and network centrality and explain what makes them useful in real-life networks.

 

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• Jacobien Carstens, University of Amsterdam – The spread of epidemic disease on networks

The key to the eradication of smallpox in 1980 was early detection and early response. The 2002 SARS epidemic did not become a pandemic due to early detection. In general, the earlier an infectious disease is detected, the smaller the outbreak. Infectious diseases spread through contact networks between individuals. Our understanding of the structure of social networks has improved the prediction of epidemic outbreaks. In this talk we will see how our understanding of networks has enhanced classical models of the spread of diseases. We will also see that when the contact network is unknown, the seemingly unrelated friendship paradox – your friends have more friends than you do – can be used for early detection of outbreaks.

 

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• Stella Kapodistria, Eindhoven University of Technology – Predicting failures in an energy network before they happen 

(no abstract provided)

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