Coloured graphlet profiles as a predictor of career length in scientific co-authorship networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Graphlets, or induced motifs, have long been used to find important medium-scale structures in directed networks. We present a method using the composition of coloured graphlets in ego-networks to characterise nodes. We give an example application using our technique to predict the numbers of years researchers are active from their collaboration networks, and compare our success with simpler metrics; particularly, we find that the use of coloured graphlets improves predictive
performance compared to colour-blind graphlets; that 4-star graphlets centred on an author are predictors of a long career, and that this effect is not degenerate to centralities.

Bibliographical metadata

Original languageEnglish
Title of host publication4th World Conference on Complex Systems: Emergence, Self-organization, Nonlinear Dynamics and Complexity
PublisherIEEE
Pages1
Number of pages6
Publication statusAccepted/In press - 14 Jan 2019