Non-backtracking centrality measures and beyond

Description of the granted funding

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.
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Starting year

2020

End year

2024

Granted funding

Vanni Noferini Orcid -palvelun logo
547 496 €

Funder

Research Council of Finland

Funding instrument

Academy projects

Other information

Funding decision number

331240

Fields of science

Mathematics

Research fields

Sovellettu matematiikka

Themes

Nuori tutkijasukupolvi 2019

Identified topics

computer science, information science, algorithms