Prof. Michael Golosovsky - 12.3.20

TBA

Citations of scientific papers - a paradigmatic complex network

Dr. Michael Golosovsky

Racah Institute of Physics, Hebrew University of Jerusalem

The interdisciplinary field of complex networks has been actively developing since 1999. Many models of network growth have been proposed by theoretical physicists, mathematicians, and computer scientists but none of them was validated against the measurements according to accepted physical standards.  We consider here one well-documented complex network -citations to scientific papers -and establish its dynamics through modeling and model-inspired measurements.

I will present a stochastic model of citation dynamics and will use it to uncover inner working of the networks of Physics, Economics, and Mathematics papers. Contrary to common belief that citation dynamics is determined by the linear preferential attachment (Markov process), we found that it follows the nonlinear autocatalytic growth (Hawkes process). The nonlinearity stems from a synergistic effect in propagation of citation cascades and is intricately related to local network topology and network motifs. The nonlinearity is the reason why the ideas advocated in highly-cited papers undergo viral propagation in scientific community, and it results in non-stationary citation distributions, diverging citation trajectories of papers, and runaways or "immortal papers".  I will also consider forecasting of the future citation behavior of  papers. I will not discuss Hirsch index and other estimators of scientific activity.