Information filtering networks
Information filtering networks
Prof. Tomaso Aste
University College London
Abstract
Networks are excellent tools to represent and model complex systems such as the human brain or financial markets. Sparse networks constructed from observational data of complex systems can be used to filter information by extracting the core interaction structure in a simplified but representative way [1]. The seminar will cover methodologies to build these networks from data [2,3]. I will also present two applications, one concerning financial markets [4] and the other instead concerning psychometric of risk for schizophrenia-spectrum disorders [5].
[1] Tumminello, Michele, Tomaso Aste, Tiziana Di Matteo, and Rosario N. Mantegna. "A tool for filtering information in complex systems." Proceedings of the National Academy of Sciences of the United States of America 102, no. 30 (2005): 10421-10426.
[2]Aste, Tomaso, Tiziana Di Matteo, and S. T. Hyde. "Complex networks on hyperbolic surfaces." Physica A: Statistical Mechanics and its Applications 346, no. 1-2 (2005): 20-26.
[3] Massara, Guido Previde, Tiziana Di Matteo, and Tomaso Aste. "Network filtering for big data: triangulated maximally filtered graph." Journal of complex Networks 5, no. 2 (2016): 161-178.
[4] Aste, Tomaso, W. Shaw, and Tiziana Di Matteo. "Correlation structure and dynamics in volatile markets." New Journal of Physics 12, no. 8 (2010): 085009.
[5] Christensen, Alexander P., Yoed N. Kenett, Tomaso Aste, Paul J. Silvia, and Thomas R. Kwapil. "Network structure of the Wisconsin Schizotypy Scales–Short Forms: Examining psychometric network filtering approaches." Behavior research methods (2018): 1-20.
Mercoledi 30 Maggio 2018 Aula F ore 15.30