Non-backtracking centrality measures and beyond

Project Details

Description

Who is the most influential person among those you follow on Twitter? Which reindeer should be isolated from the herd to avoid the spread of a deadly disease?

These are examples of the typical questions that network theory can answer via centrality measures: functions defined on every node of a graph that capture the relative importance of each individual within a network. Although this is a classical subject in applied mathematics, first studied in the context of social sciences and later generalized to tackle problems in a wide pool of disciplines, recently Professor Noferini and collaborators discovered a completely new class of centrality measures that have the potential to overcome certain disadvantages that more classical measures are known to have.

The purpose of this project is to advance further in the study of these novel measures, and to apply them concretely to study problems in biology, economics, and finance.
Short titleOPH / EDUFI Shen
StatusFinished
Effective start/end date01/09/201730/09/2018

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