Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/192284
DC FieldValue
dc.titleMean Consensus Time of the Voter Model on Networks Partitioned into Two Cliques of Arbitrary Sizes
dc.contributor.authorM. T. Gastner
dc.contributor.authorK. Ishida
dc.contributor.editorCherifi, Hocine
dc.contributor.editorMendes, José Fernando
dc.contributor.editorRocha, Luis Mateus
dc.contributor.editorGaito, Sabrina
dc.contributor.editorMoro, Esteban
dc.contributor.editorGonçalves-Sá, Joana
dc.contributor.editorSantos, Francisco
dc.date.accessioned2021-06-29T03:14:35Z
dc.date.available2021-06-29T03:14:35Z
dc.date.issued2019-12-10
dc.identifier.citationM. T. Gastner, K. Ishida (2019-12-10). Mean Consensus Time of the Voter Model on Networks Partitioned into Two Cliques of Arbitrary Sizes. Complex Networks 2019 : 46-48. ScholarBank@NUS Repository.
dc.identifier.isbn9.78296E+12
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/192284
dc.description.abstractThe voter model is a paradigmatic agent-based model that represents opinion dynamics in social networks. While early studies of the voter model focused on complete graphs or regular lattices, interest has recently shifted towards networks with more complex topologies (e.g. networks with a community structure). Here we analyze the voter model on the simplest possible multi-community network: two cliques (i.e. fully connected subgraphs) connected by a small number of intercommunity edges.
dc.description.urihttps://drive.google.com/file/d/1wJ0eCPruTARpvuq48ku9grFcKVcWC3re/view
dc.language.isoen
dc.publisherInternational Conference on Complex Networks & Their Applications
dc.subjectvoter model, opinion formation, community structure
dc.typeConference Paper
dc.contributor.departmentYALE-NUS COLLEGE
dc.description.sourcetitleComplex Networks 2019
dc.description.page46-48
dc.published.statePublished
Appears in Collections:Elements
Staff Publications

Show simple item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
GastnerIshida2019b.pdf1.41 MBAdobe PDF

OPEN

PublishedView/Download

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.