- 1. Statistical Physics Lab, Department of Physics, University
of SeoulMesoscale Structures of NetworksSang Hoon LeeDepartment of
Energy Science, Sungkyunkwan
Universityhttp://sites.google.com/site/lshlj82SHL, M. Cucuringu,
and M. A. Porter, Density-based and transport-based core-periphery
structures in networks, Phys. Rev. E 89, 032810 (2014);SHL, M. D.
Fricker, and M. A. Porter, Mesoscale Analyses of Fungal Networks,
e-print arXiv:1406.5855;M. Cucuringu, M. P. Rombach, SHL, and M. A.
Porter, Detection of Core-Periphery Structure in Networks Using
Spectral Methods andGeodesic Paths, e-print arXiv:1410.6572;SHL, M.
Farazmand, G. Haller, and M. A. Porter, Finding Lagrangian Coherent
Structures Using Community Detection, in preparation.
2. Outline core vs periphery structure in networks density-based
vs transport-based coreness measures application to various real
networks related to nestedess in ecological networks? community
detection in networks mesoscopic response function (MRF) based
taxonomy fungal networks (nutrient/energy transport) multilayer
community detection Lagrangian coherent structures (ocean flow)
political cosponsorship networks summary and outlook 3. mesoscale
structures of a network in terms of transport1234567 4. mesoscale
structures of a network in terms of transport1234567 5. mesoscale
structures of a network in terms of transport1234567 6. mesoscale
structures of a network in terms of transport123two modes or
modules(or communities)4567R. Lambiotte, J.-C. Delvenne, and M.
Barahona, arXiv:0812.1770;M. Rosvall and C. T. Bergstrom, PNAS 104,
7327 (2007); PNAS 105, 1118 (2008). 7. Community structure in
networks adjacency matrixp1=0.5, p2=0.05, p3=0.5; pS=0, dS=00 20 40
60 80 1000102030405060708090100nz = 2730 8. Community structure in
networks adjacency matrixp1=0.5, p2=0.05, p3=0.5; pS=0, dS=00 20 40
60 80 1000102030405060708090100nz = 2730modularity (the objective
function to be maximized)Q =12XijWij