Complex networks and agent-based models

• New Scientist 24.4.2007: Cellphone study shows the ties that bind nations
• Spiegel Online 25.4.2007: Flüchtige Bekanntschaften halten die Info-Gesellschaft zusammen
• Yleisradio (Finnish national radio broadcaster): Interview in Tieteen viikko (Weekly Science News)
• PhysicsWeb newsflash
• Science News Focus 10. November 1006, Tracking People's Electronic Footprints

A Brief Introduction to Complex Networks

Networks are ubiquitous in Nature. This WWW page has travelled to your computer through an intricate network of connected computers - a network for which there is no overall blueprint and where there is no central authority, but which is nevertheless very robust and efficient. We, human beings, are made of networks - the neural network of our brain, the complex network of metabolic reactions providing us with energy, the multitude of genes acting in concert, coupled through regulatory processes. We also participate in networks: social ties connect us to our colleagues, friends, and family, and finally to the enormous social network spanning the entire planet.

The Complex Networks and Agent-Based Models group, led by Dr. Jari Saramäki, studies these fascinating, self-organizing structures.

During the recent years, complex systems have been approached from several perspectives. Especially the complex networks view has turned out to be extremely fruitful, revealing general principles applicable to a large number of systems ranging from the Internet to protein-protein interaction networks of living cells. In this approach, diverse systems are viewed as networks, so that the interacting elements such as proteins are described by network vertices and their interactions by edges connecting the vertices.

Studies of the characteristics of networks have produced novel, unexpected findings such as the common small-world property, the ubiquity of scale-free connectivity distributions and the high degrees of clustering found in natural networks. The properties of networked systems are typically investigated using theoretical and computational methods closely related to those of statistical physics.

Overall, the main strength of the complex networks approach is its ability to capture the properties of large-scale complex systems by using only simply building blocks, the vertices and edges, and then derive system-level properties from their interrelations.

Want to know more?

• More on our research.
• Kompleksisten verkostojen fysiikkaa, an introduction to complex & social networks published in Arkhimedes 01/2007 (sorry, in Finnish only!)
• PhysicsWeb newsflash on our mobile-phone social network study.
• Science News Focus 10. November 2006, Social science: Tracking People's Electronic Footprints, also on the phone network studies.
• Structure and tie strengths in mobile communication networks, J.-P. Onnela, J. Saramäki, J. Hyvönen, G. Szabó, D. Lazer, K. Kaski, J. Kertész, and A.-L. Barabási, Proc. Natl. Acad. Sci. (USA), in press (2007), physics/0610104
• Limited resolution in complex network community detection with Potts model approach, J.M. Kumpula, J. Saramäki, K. Kaski and J. Kertész, Eur. Phys. J. B, in press (2007), cond-mat/0610370
• Spectral and network methods in the analysis of correlation matrices of stock returns, T. Heimo, J. Saramäki, J.-P. Onnela, and K. Kaski, Physica A, in press (2007), physics/0703061
• More papers by our group