Zur Kurzanzeige

dc.contributor.authorLodewijks, Bas
dc.contributor.editoraus dem Siepen, Elisabeth
dc.contributor.editorRandecker, Anja
dc.date.accessioned2026-09-11T11:59:23Z
dc.date.available2026-09-11T11:59:23Z
dc.date.issued2026-09-11
dc.identifier.urihttps://publications.mfo.de/handle/mfo/4458
dc.description.abstractNetworks can be found all around us. From the friendships we form, both in person and online, to the websites we visit on the Internet, and the telephones we use to send messages and make phone calls. Understanding the behavior and structure of these networks can be a difficult task. Mathematicians use models of such complex real-world networks to provide novel insights from an analytical point of view. In this snapshot, we take a look at why mathematics can be useful in understanding networks and discuss interesting recent developments in the study of a popular class of models known as preferential attachment models, which try to explain why the rich get richer.en_US
dc.language.isoenen_US
dc.publisherMathematisches Forschungsinstitut Oberwolfachen_US
dc.relation.ispartofseriesSnapshots of modern mathematics from Oberwolfach;2026-10
dc.rightsAttribution-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/*
dc.titleDo the rich get richer? Mathematical models for real-world networksen_US
dc.typeArticleen_US
dc.identifier.doi10.14760/SNAP-2026-010-EN
local.series.idSNAP-2026-010-ENen_US
local.subject.snapshotProbability Theory and Statisticsen_US
dc.identifier.ppn1983845361


Dateien zu dieser Ressource

Thumbnail
Thumbnail

Das Dokument erscheint in:

Zur Kurzanzeige

Attribution-ShareAlike 4.0 International
Solange nicht anders angezeigt, wird die Lizenz wie folgt beschrieben: Attribution-ShareAlike 4.0 International